scholarly journals An analysis of ground truth binarized image variability of palm leaf manuscripts

2015 ◽  
Author(s):  
Made Windu Antara Kesiman ◽  
Sophea Prum ◽  
I Made Gede Sunarya ◽  
Jean-Christophe Burie ◽  
Jean-Marc Ogier
Keyword(s):  
Ground Truth ◽  
Image Variability ◽  
Palm Leaf ◽  
Binarized Image

scholarly journals Ecological, Cultural, and Geographical Implications of Brahea dulcis (Kunth) Mart. Insights for Sustainable Management in Mexico

2020 ◽  
Vol 12 (1) ◽  
pp. 412 ◽  
Author(s):  
Cloe X. Pérez-Valladares ◽  
Ana I. Moreno-Calles ◽  
Alejandro Casas ◽  
Selene Rangel-Landa ◽  
José Blancas ◽  
...  
Keyword(s):  
Rural Communities ◽  
Sustainable Management ◽  
Management Practices ◽  
Ground Truth ◽  
Structured Interviews ◽  
Five Factors ◽  
Palm Species ◽  
Two Stages ◽  
Palm Leaf

Palm plants provide important benefits for rural communities around the world. Of the 95 native palm species in Mexico, Brahea dulcis (Soyate palm) has been tagged as an important resource for many Mesoamerican ethnical groups. Scientific and empirical knowledge concerning Soyate is thematically fragmented and disassociated, meaning that sound sustainable management is far from established. Research of over 20 years has permitted us to document ecological, cultural and geographical outcomes of B. dulcis; thus, the present paper aims at compiling all knowledge on Soyate to eventually guide its long-term management. It was conducted in two stages: firstly, it comprised a thorough review of previous studies on the management of B. dulcis in Mexico; secondly, we integrated unpublished outcomes obtained from fieldwork, including participatory ground-truth validation and semi-structured interviews obtained from local ethnic groups. Five factors guided our compilation effort: (i) biological and ecological information, (ii) cultural importance, (iii) economic triggers, (iv) traditional management, and (v) ecological and ecogeographical implications of Soyate palm management. The present paper confirms that B. dulcis is an important cultural resource whose utilization can be traced back over 10,000 years. The leaves of Soyate are the most useful part of the palm and were profusely used in the past for thatching roofs and weaving domestic and agricultural objects. Currently, however, palm-leaf weaving is primarily oriented toward satisfying economic needs. We depicted ten management practices aimed at favoring palm availability. Most of these management practices have enhanced sustainable palm leaf harvesting; however, these practices harbor spatial trends that turn highly diverse habitats into Soyate-dominated spaces. To conclude, we propose a framework to describe sound and sustainable Soyate management in the light of the current long-term Soyate–human relationship. It is here acknowledged that Soyate has played and continues to play a critical socioeconomic and cultural role for many ethnical groups in Central Mexico. Nonetheless, emerging challenges concerning the sustainability of the whole socioecological system at a landscape level are yet to be overcome.

A Comparison of Simple Structure Rotation Criteria in Temporal Exploratory Factor Analysis for Event-Related Potential Data

Methodology ◽  
2019 ◽  
Vol 15 (Supplement 1) ◽  
pp. 43-60 ◽  
Author(s):  
Florian Scharf ◽  
Steffen Nestler
Keyword(s):  
Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Simple Structure ◽  
Ground Truth ◽  
Event Related Potential ◽  
Suitable Alternative ◽  
Factor Rotation ◽  
Rotation Methods ◽  
Simple Structure Rotation ◽  
Temporal Overlap

Abstract. It is challenging to apply exploratory factor analysis (EFA) to event-related potential (ERP) data because such data are characterized by substantial temporal overlap (i.e., large cross-loadings) between the factors, and, because researchers are typically interested in the results of subsequent analyses (e.g., experimental condition effects on the level of the factor scores). In this context, relatively small deviations in the estimated factor solution from the unknown ground truth may result in substantially biased estimates of condition effects (rotation bias). Thus, in order to apply EFA to ERP data researchers need rotation methods that are able to both recover perfect simple structure where it exists and to tolerate substantial cross-loadings between the factors where appropriate. We had two aims in the present paper. First, to extend previous research, we wanted to better understand the behavior of the rotation bias for typical ERP data. To this end, we compared the performance of a variety of factor rotation methods under conditions of varying amounts of temporal overlap between the factors. Second, we wanted to investigate whether the recently proposed component loss rotation is better able to decrease the bias than traditional simple structure rotation. The results showed that no single rotation method was generally superior across all conditions. Component loss rotation showed the best all-round performance across the investigated conditions. We conclude that Component loss rotation is a suitable alternative to simple structure rotation. We discuss this result in the light of recently proposed sparse factor analysis approaches.

Brain FDG PET for the Etiological Diagnosis of Clinically Uncertain Cognitive Impairment During Delirium in Remission

2020 ◽  
Vol 77 (4) ◽  
pp. 1609-1622
Author(s):  
Franziska Mathies ◽  
Catharina Lange ◽  
Anja Mäurer ◽  
Ivayla Apostolova ◽  
Susanne Klutmann ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Fdg Pet ◽  
False Negative ◽  
Ground Truth ◽  
Etiological Diagnosis ◽  
Geriatric Unit ◽  
Positron Emission ◽  
The Brain ◽  
Hospitalized Geriatric Patients

Background: Positron emission tomography (PET) of the brain with 2-[F-18]-fluoro-2-deoxy-D-glucose (FDG) is widely used for the etiological diagnosis of clinically uncertain cognitive impairment (CUCI). Acute full-blown delirium can cause reversible alterations of FDG uptake that mimic neurodegenerative disease. Objective: This study tested whether delirium in remission affects the performance of FDG PET for differentiation between neurodegenerative and non-neurodegenerative etiology of CUCI. Methods: The study included 88 patients (82.0±5.7 y) with newly detected CUCI during hospitalization in a geriatric unit. Twenty-seven (31%) of the patients were diagnosed with delirium during their current hospital stay, which, however, at time of enrollment was in remission so that delirium was not considered the primary cause of the CUCI. Cases were categorized as neurodegenerative or non-neurodegenerative etiology based on visual inspection of FDG PET. The diagnosis at clinical follow-up after ≥12 months served as ground truth to evaluate the diagnostic performance of FDG PET. Results: FDG PET was categorized as neurodegenerative in 51 (58%) of the patients. Follow-up after 16±3 months was obtained in 68 (77%) of the patients. The clinical follow-up diagnosis confirmed the FDG PET-based categorization in 60 patients (88%, 4 false negative and 4 false positive cases with respect to detection of neurodegeneration). The fraction of correct PET-based categorization did not differ between patients with delirium in remission and patients without delirium (86% versus 89%, p = 0.666). Conclusion: Brain FDG PET is useful for the etiological diagnosis of CUCI in hospitalized geriatric patients, as well as in patients with delirium in remission.

A Flying Gray Ball Multi-illuminant Image Dataset for Color Research

2020 ◽  
Vol 64 (5) ◽  
pp. 50411-1-50411-8
Author(s):  
Hoda Aghaei ◽  
Brian Funt
Keyword(s):  
Machine Vision ◽  
Spectral Reflectance ◽  
Color Constancy ◽  
Ground Truth ◽  
Practical Approach ◽  
Post Processing ◽  
Illumination Estimation ◽  
Processing Step ◽  
Image Dataset

Abstract For research in the field of illumination estimation and color constancy, there is a need for ground-truth measurement of the illumination color at many locations within multi-illuminant scenes. A practical approach to obtaining such ground-truth illumination data is presented here. The proposed method involves using a drone to carry a gray ball of known percent surface spectral reflectance throughout a scene while photographing it frequently during the flight using a calibrated camera. The captured images are then post-processed. In the post-processing step, machine vision techniques are used to detect the gray ball within each frame. The camera RGB of light reflected from the gray ball provides a measure of the illumination color at that location. In total, the dataset contains 30 scenes with 100 illumination measurements on average per scene. The dataset is available for download free of charge.

Nanosecond Photodynamics Simulations of a Cis-Trans Isomerization Are Enabled by Machine Learning

2020 ◽  
Author(s):  
Jingbai Li ◽  
Patrick Reiser ◽  
André Eberhard ◽  
Pascal Friederich ◽  
Steven Lopez
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Excited State ◽  
Adaptive Sampling ◽  
Computational Cost ◽  
Ground Truth ◽  
Absolute Error ◽  
Photochemical Reactions ◽  
Computational Techniques ◽  
Full Potential

<p>Photochemical reactions are being increasingly used to construct complex molecular architectures with mild and straightforward reaction conditions. Computational techniques are increasingly important to understand the reactivities and chemoselectivities of photochemical isomerization reactions because they offer molecular bonding information along the excited-state(s) of photodynamics. These photodynamics simulations are resource-intensive and are typically limited to 1–10 picoseconds and 1,000 trajectories due to high computational cost. Most organic photochemical reactions have excited-state lifetimes exceeding 1 picosecond, which places them outside possible computational studies. Westermeyr <i>et al.</i> demonstrated that a machine learning approach could significantly lengthen photodynamics simulation times for a model system, methylenimmonium cation (CH<sub>2</sub>NH<sub>2</sub><sup>+</sup>).</p><p>We have developed a Python-based code, Python Rapid Artificial Intelligence <i>Ab Initio</i> Molecular Dynamics (PyRAI<sup>2</sup>MD), to accomplish the unprecedented 10 ns <i>cis-trans</i> photodynamics of <i>trans</i>-hexafluoro-2-butene (CF<sub>3</sub>–CH=CH–CF<sub>3</sub>) in 3.5 days. The same simulation would take approximately 58 years with ground-truth multiconfigurational dynamics. We proposed an innovative scheme combining Wigner sampling, geometrical interpolations, and short-time quantum chemical trajectories to effectively sample the initial data, facilitating the adaptive sampling to generate an informative and data-efficient training set with 6,232 data points. Our neural networks achieved chemical accuracy (mean absolute error of 0.032 eV). Our 4,814 trajectories reproduced the S<sub>1</sub> half-life (60.5 fs), the photochemical product ratio (<i>trans</i>: <i>cis</i> = 2.3: 1), and autonomously discovered a pathway towards a carbene. The neural networks have also shown the capability of generalizing the full potential energy surface with chemically incomplete data (<i>trans</i> → <i>cis</i> but not <i>cis</i> → <i>trans</i> pathways) that may offer future automated photochemical reaction discoveries.</p>

A Study On Consumer Awareness Towards Siddha Medicine In Dharmapuri City

2019 ◽  
Vol 118 (12) ◽  
pp. 16-23
Author(s):  
M. Chitra ◽  
Dr. C. Madhesh
Keyword(s):  
South India ◽  
T Test ◽  
Statistical Techniques ◽  
Consumer Awareness ◽  
Chi Square ◽  
Modern Era ◽  
Palm Leaf

Siddha is considered to be one of the oldest medicines with its own benefits. In this modern era, people are more aware towards their health. At many circumstances of illness, people use Siddha medicines to cure their disease. Siddha is preferred for its own specialties. This paper has attempted to reveal the awareness towards Siddha medicines taking 52 respondents from Dharmapuri City. The results were analysed by using various statistical techniques like percentage analysis, chi-square and t test. Siddha focuses on the eight supernatural powers called as ‘Ashtaamahasiddhi’ and those who achieved these powers were known as siddhars. Hence it is called as siddha medicine. The siddhars knowledge was found in palm leaf manuscripts and their fragments were found in some parts of south India.

Model and Method for Contributor’s Quality Assessment in Community Image Tagging Systems

2018 ◽  
pp. 45-51
Author(s):  
A. V. Ponomarev
Keyword(s):  
Large Scale ◽  
Wide Spectrum ◽  
Preference Relation ◽  
Pairwise Comparison ◽  
Ground Truth ◽  
Comparison Method ◽  
Characteristic Matrix ◽  
Image Tagging ◽  
Proposed Model

Introduction: Large-scale human-computer systems involving people of various skills and motivation into the information processing process are currently used in a wide spectrum of applications. An acute problem in such systems is assessing the expected quality of each contributor; for example, in order to penalize incompetent or inaccurate ones and to promote diligent ones.Purpose: To develop a method of assessing the expected contributor’s quality in community tagging systems. This method should only use generally unreliable and incomplete information provided by contributors (with ground truth tags unknown).Results:A mathematical model is proposed for community image tagging (including the model of a contributor), along with a method of assessing the expected contributor’s quality. The method is based on comparing tag sets provided by different contributors for the same images, being a modification of pairwise comparison method with preference relation replaced by a special domination characteristic. Expected contributors’ quality is evaluated as a positive eigenvector of a pairwise domination characteristic matrix. Community tagging simulation has confirmed that the proposed method allows you to adequately estimate the expected quality of community tagging system contributors (provided that the contributors' behavior fits the proposed model).Practical relevance: The obtained results can be used in the development of systems based on coordinated efforts of community (primarily, community tagging systems). 

Determining Ground Truth" in the New Jersey STRATAFORM Natural Laboratory"

1999 ◽  
Author(s):  
Jr Austin ◽  
Fulthorpe James A. ◽  
Olson Craig S. ◽  
Hilary
Keyword(s):  
New Jersey ◽  
Ground Truth ◽  
Natural Laboratory
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