scholarly journals Repeatable Semantic Reef-Mapping through Photogrammetry and Label-Augmentation

2021 ◽  
Vol 13 (4) ◽  
pp. 659 ◽  
Author(s):  
Matan Yuval ◽  
Iñigo Alonso ◽  
Gal Eyal ◽  
Dan Tchernov ◽  
Yossi Loya ◽  
...  
Keyword(s):  
Computer Vision ◽  
Slope Angle ◽  
Cost Effective ◽  
Semantic Segmentation ◽  
Point Of View ◽  
Marine Ecology ◽  
Benthic Habitats ◽  
Ecological Processes ◽  
Data Set ◽  
Natural Systems

In an endeavor to study natural systems at multiple spatial and taxonomic resolutions, there is an urgent need for automated, high-throughput frameworks that can handle plethora of information. The coalescence of remote-sensing, computer-vision, and deep-learning elicits a new era in ecological research. However, in complex systems, such as marine-benthic habitats, key ecological processes still remain enigmatic due to the lack of cross-scale automated approaches (mms to kms) for community structure analysis. We address this gap by working towards scalable and comprehensive photogrammetric surveys, tackling the profound challenges of full semantic segmentation and 3D grid definition. Full semantic segmentation (where every pixel is classified) is extremely labour-intensive and difficult to achieve using manual labeling. We propose using label-augmentation, i.e., propagation of sparse manual labels, to accelerate the task of full segmentation of photomosaics. Photomosaics are synthetic images generated from a projected point-of-view of a 3D model. In the lack of navigation sensors (e.g., a diver-held camera), it is difficult to repeatably determine the slope-angle of a 3D map. We show this is especially important in complex topographical settings, prevalent in coral-reefs. Specifically, we evaluate our approach on benthic habitats, in three different environments in the challenging underwater domain. Our approach for label-augmentation shows human-level accuracy in full segmentation of photomosaics using labeling as sparse as 0.1%, evaluated on several ecological measures. Moreover, we found that grid definition using a leveler improves the consistency in community-metrics obtained due to occlusions and topology (angle and distance between objects), and that we were able to standardise the 3D transformation with two percent error in size measurements. By significantly easing the annotation process for full segmentation and standardizing the 3D grid definition we present a semantic mapping methodology enabling change-detection, which is practical, swift, and cost-effective. Our workflow enables repeatable surveys without permanent markers and specialized mapping gear, useful for research and monitoring, and our code is available online. Additionally, we release the Benthos data-set, fully manually labeled photomosaics from three oceanic environments with over 4500 segmented objects useful for research in computer-vision and marine ecology.

Territorial Distribution of Alcohol and Drug Addictions Mortality Concerning Regional Disparities in the Slovak Republic from Year 1996 to Year 2015

2020 ◽  
Keyword(s):  
Mortality Rate ◽  
Slovak Republic ◽  
Regional Disparities ◽  
Point Of View ◽  
Extreme Position ◽  
Data Set ◽  
Female Sex ◽  
Male Sex ◽  
The Individual ◽  
High Level

BACKGROUND: This paper deals with territorial distribution of the alcohol and drug addictions mortality at a level of the districts of the Slovak Republic. AIM: The aim of the paper is to explore the relations within the administrative territorial division of the Slovak Republic, that is, between the individual districts and hence, to reveal possibly hidden relation in alcohol and drug mortality. METHODS: The analysis is divided and executed into the two fragments – one belongs to the female sex, the other one belongs to the male sex. The standardised mortality rate is computed according to a sequence of the mathematical relations. The Euclidean distance is employed to compute the similarity within each pair of a whole data set. The cluster analysis examines is performed. The clusters are created by means of the mutual distances of the districts. The data is collected from the database of the Statistical Office of the Slovak Republic for all the districts of the Slovak Republic. The covered time span begins in the year 1996 and ends in the year 2015. RESULTS: The most substantial point is that the Slovak Republic possesses the regional disparities in a field of mortality expressed by the standardised mortality rate computed particularly for the diagnoses assigned to the alcohol and drug addictions at a considerably high level. However, the female sex and the male sex have the different outcome. The Bratislava III District keeps absolutely the most extreme position. It forms an own cluster for the both sexes too. The Topoľčany District bears a similar extreme position from a point of view of the male sex. All the Bratislava districts keep their mutual notable dissimilarity. Contrariwise, evaluation of a development of the regional disparities among the districts looks like notably heterogeneously. CONCLUSIONS: There are considerable regional discrepancies throughout the districts of the Slovak Republic. Hence, it is necessary to create a common platform how to proceed with the solution of this issue.

The Role of Economic Evaluation in Dissemination and Implementation Research

2017 ◽  
Author(s):  
Ramesh Raghavan
Keyword(s):  
Service Providers ◽  
Implementation Strategies ◽  
Cost Effective ◽  
Point Of View ◽  
Dissemination And Implementation ◽  
Economic Point ◽  
Open Questions ◽  
Public Health Organizations ◽  
Quality Health ◽  
Dissemination And Implementation Research

This chapter presents an overview of how D&I research can be evaluated from an economic point of view. Dissemination and implementation imposes costs upon knowledge purveyors, provider organizations, public health organizations, and payers (including governments). However, whether these added costs will result in improved service delivery and, perhaps more importantly, client outcomes and improvements in population health remain as open questions. If emerging studies reveal that defined implementation strategies are more cost effective than “usual” implementation, then policymakers and service providers will need to resource these added costs of implementation in order to assure the success and sustainability of high-quality health services over the long term.

Configurations to Superior Environmental Innovation Strategy: A Both–And Approach

2021 ◽  
pp. 108602662110316
Author(s):  
Tiziana Russo-Spena ◽  
Nadia Di Paola ◽  
Aidan O’Driscoll
Keyword(s):  
Climate Change ◽  
Value Chain ◽  
Critical Role ◽  
Well Being ◽  
Point Of View ◽  
Future Generations ◽  
Innovation Strategy ◽  
Environmental Innovation ◽  
Data Set

An effective climate change action involves the critical role that companies must play in assuring the long-term human and social well-being of future generations. In our study, we offer a more holistic, inclusive, both–and approach to the challenge of environmental innovation (EI) that uses a novel methodology to identify relevant configurations for firms engaging in a superior EI strategy. A conceptual framework is proposed that identifies six sets of driving characteristics of EI and two sets of beneficial outcomes, all inherently tensional. Our analysis utilizes a complementary rather than an oppositional point of view. A data set of 65 companies in the ICT value chain is analyzed via fuzzy-set comparative analysis (fsQCA) and a post-QCA procedure. The results reveal that achieving a superior EI strategy is possible in several scenarios. Specifically, after close examination, two main configuration groups emerge, referred to as technological environmental innovators and organizational environmental innovators.

scholarly journals Comparison between Concentrated Solar Power and Gas-Based Generation in Terms of Economic and Flexibility-Related Aspects in Chile

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1063
Author(s):  
Catalina Hernández Moris ◽  
Maria Teresa Cerda Guevara ◽  
Alois Salmon ◽  
Alvaro Lorca
Keyword(s):  
Natural Gas ◽  
Solar Power ◽  
Renewable Energy Sources ◽  
Cost Effective ◽  
Hybrid Plant ◽  
Point Of View ◽  
Concentrated Solar Power ◽  
Economic Point ◽  
Hybrid Plants ◽  
Cost Of Energy

The energy sector in Chile demands a significant increase in renewable energy sources in the near future, and concentrated solar power (CSP) technologies are becoming increasingly competitive as compared to natural gas plants. Motivated by this, this paper presents a comparison between solar technologies such as hybrid plants and natural gas-based thermal technologies, as both technologies share several characteristics that are comparable and beneficial for the power grid. This comparison is made from an economic point of view using the Levelized Cost of Energy (LCOE) metric and in terms of the systemic benefits related to flexibility, which is very much required due to the current decarbonization scenario of Chile’s energy matrix. The results show that the LCOE of the four hybrid plant models studied is lower than the LCOE of the gas plant. A solar hybrid plant configuration composed of a photovoltaic and solar tower plant (STP) with 13 h of storage and without generation restrictions has an LCOE 53 USD/MWh, while the natural gas technology evaluated with an 85% plant factor and a variable fuel cost of 2.0 USD/MMBtu has an LCOE of 86 USD/MWh. Thus, solar hybrid plants under a particular set of conditions are shown to be more cost-effective than their closest competitor for the Chilean grid while still providing significant dispatchability and flexibility.

scholarly journals A Benchmark and Evaluation of Non-Rigid Structure from Motion

2020 ◽  
Author(s):  
Sebastian Hoppe Nesgaard Jensen ◽  
Mads Emil Brix Doest ◽  
Henrik Aanæs ◽  
Alessio Del Bue
Keyword(s):  
Computer Vision ◽  
Structure From Motion ◽  
State Of The Art ◽  
The State ◽  
Quality Data ◽  
Data Set ◽  
Rigid Structure ◽  
Public Data ◽  
3D Information ◽  
Further Development

AbstractNon-rigid structure from motion (nrsfm), is a long standing and central problem in computer vision and its solution is necessary for obtaining 3D information from multiple images when the scene is dynamic. A main issue regarding the further development of this important computer vision topic, is the lack of high quality data sets. We here address this issue by presenting a data set created for this purpose, which is made publicly available, and considerably larger than the previous state of the art. To validate the applicability of this data set, and provide an investigation into the state of the art of nrsfm, including potential directions forward, we here present a benchmark and a scrupulous evaluation using this data set. This benchmark evaluates 18 different methods with available code that reasonably spans the state of the art in sparse nrsfm. This new public data set and evaluation protocol will provide benchmark tools for further development in this challenging field.

Clinical Profile and Prediction of Response to Treatment in Childhood Epilepsy - A Single-Centre Experience from Eastern India

2021 ◽  
Vol 8 (15) ◽  
pp. 977-981
Author(s):  
Prakash Chandra Ghosh ◽  
Mitali Bera ◽  
Punyabrata Barma ◽  
Arijit Roy ◽  
Sananda Majumder ◽  
...  
Keyword(s):  
Management Strategies ◽  
Poor Response ◽  
Cost Effective ◽  
Point Of View ◽  
Clinical Profile ◽  
Response To Treatment ◽  
Childhood Epilepsy ◽  
Primary Health Centres ◽  
Single Centre Experience ◽  
Active Epilepsy

BACKGROUND Though epilepsy remains a significant problem for children and adolescents in our country, studies delineating the clinical profile and response to treatment in childhood epilepsy are lacking. The current study was carried out for obtaining a baseline profile and to predict the response to treatment in childhood epilepsy in India that may be helpful in planning management strategies from a public health point of view. METHODS Patients with clinical suggestion of active epilepsy (N = 141) from one month to 12 years, were enrolled into the study over a period of 1 year (February 2010 to January 2011) from the out-patient department and epilepsy clinic of Bangur Institute of Neurology. Detailed history was taken along with neurological examination. Electroencephalography (EEG) and neuroimaging (MRI / CT scan) were done on all patients. Each patient included in the study was kept in followup for a period of 6 months and their response to the treatment was recorded. RESULTS About 48.9 % (N = 69) patients had localisation related epilepsy while the rest had generalised epilepsy. Of those with generalised epilepsy, generalised tonicclonic seizures (GTCS) was by far the most common type. Of those with focal EEG activity, the highest proportion (50 %), were localised to the temporal lobe. Symptomatic aetiology accounted for 59.6 % (N = 84) of the patients. 20.6 % (N = 29) had poor response to treatment at 6 months follow-up. Abnormal neuroimaging (OR = 6.708) and abnormal EEG (OR = 6.357) were effective factors in predicting poor response to treatment. CONCLUSIONS Our study highlights the need to link specialised epilepsy services with primary health centres for early detection and treatment. EEG is an essential cost-effective modality in determining seizure localisation and response to treatment. KEYWORDS Paediatric, Epilepsy, Clinical Profile, Response to Treatment

Multidisciplinary Approach in The Permian Basin - A Geological, Statistical and Engineering Case Study to Production Results on the Wichita-Albany Formation

2015 ◽  
Author(s):  
Fabián Vera ◽  
Casee Lemons ◽  
Ming Zhong ◽  
William D. Holcomb ◽  
Randy F. LaFollette
Keyword(s):  
Design Patterns ◽  
Point Of View ◽  
Production Optimization ◽  
Multivariate Statistical ◽  
Data Set ◽  
Modern Approach ◽  
Well Production ◽  
Fracture Fluid ◽  
Major Factors ◽  
The Impact

Abstract This study compares reservoir characteristics, completion methods and production for 431 wells in 6 counties producing from the Wichita-Albany reservoir to assess major factors in production optimization and derive ultimate recovery estimates. The purpose of the study is to analyze completion design patterns across the study area by combining public and proprietary data for mining. Integrating several analyses of different nature and their respective methods like statistics, geology and engineering create a modern approach as well as a more holistic point of view when certain measurements are missing from the data set. Furthermore, multivariate statistical analysis allows modeling the impact of particular completion and stimulation parameters on the production outcome by averaging out the impact of all other variables in the system. In addition to completion type, more than 18 predictor variables were examined, including treatment parameters such as fracture fluid volume, year of completion, cumulative perforated length, proppant type, proppant amount, and county location, among others. In this sense, this contribution seems unique in unifying statistical, engineering, and geological perspectives into a singular point of view. This work also provides complementary views for well production consideration.

Reflective backward analysis to assess the operational performance and eco-efficiency of two industrial districts

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Andrea Appolloni ◽  
Idiano D'Adamo ◽  
Massimo Gastaldi ◽  
Morteza Yazdani ◽  
Davide Settembre-Blundo
Keyword(s):  
Economic Trend ◽  
Careful Analysis ◽  
Point Of View ◽  
Industrial Districts ◽  
Management Approach ◽  
Ceramic Tiles ◽  
Data Set ◽  
Content Type ◽  
Sectorial Analysis ◽  
Backward Analysis

PurposeThe best strategy to apply for the future cannot disregard a careful analysis of the past and is the one capable of seizing opportunities from outside. Manufacturing sectors are characterized by sudden changes, and in this work, we analyze the ceramic tiles sector characterized by a mature technology in which innovation has played a key role.Design/methodology/approachThis study aims to provide a sectorial analysis based on a historical data set (2004–2019) to highlight how an industry is performing both operationally and in terms of eco-efficiency. For this purpose, from a methodological point of view, the data envelopment analysis (DEA) was used.FindingsThe results of the analysis show that the Spanish ceramics industry shows a growing economic trend by taking advantage of lower industrial costs, while the Italian industry is characterized by a modest decline partially mitigated by exports. The industrial districts are an aggregation of companies that in the ceramic sector has allowed to combine innovation, sustainability and digitalization and is a model toward the maximization of sustainable efficiency because it is a place of aggregation of resources and ideas.Originality/valueThis study experiments with an innovative way of addressing traditional industry analysis, namely, integrating the reflective management approach with DEA-based backward analysis. This provides decision makers with the basis for new interpretations of variable trends.

Data normalization for training and analysis of the MaskRCNN model using the k-means method for computer vision of smart refrigerator

2021 ◽  
Vol 4 ◽  
pp. 74-80
Author(s):  
M. G. Dorrer ◽  
◽  
A.E. Alekhina ◽  
Keyword(s):  
Computer Vision ◽  
Semantic Segmentation ◽  
Correct Choice ◽  
Training Sample ◽  
Artificial Vision ◽  
K Value ◽  
High K ◽  
Real World Datasets ◽  
Segmentation Problem

This paper proposes using the k-means method for the controlled adjustment of the training sample for semantic image segmentation in the artificial vision of a smart refrigerator. To solve this problem, a new two-stage architecture for computer vision is proposed. In the proposed architecture, various sets of settings for optimizing the contrast of images are used to classify pixels according to their belonging to fragments of the studied image. Extensive experimental evaluation shows that the proposed method has critical advantages over existing work. Firstly, the obtained pixel classes can be directly clustered into semantic groups using k-means. Secondly, the method can be used for additional training of artificial intelligence in solving the semantic segmentation problem. The developers propose an approach to the correct choice of the number k of centroids to obtain good quality clusters, which is difficult to determine at a high k value. To overcome the problem of initializing the k-means method, an incremental k-means clustering method is proposed, which improves the quality of clusters to reduce the sum of squared errors. Comprehensive experiments have been carried out compared to the traditional k-means algorithm and its new versions to evaluate the performance of the proposed method on synthetically generated datasets and some real-world datasets.

Anaerobic digestion for sustainable development: a natural approach

2002 ◽  
Vol 45 (10) ◽  
pp. 321-328 ◽  
Author(s):  
H.J. Gijzen
Keyword(s):  
Industrial Wastewater ◽  
Systems Approach ◽  
Cost Effective ◽  
Anaerobic Treatment ◽  
High Rate ◽  
Natural Ecosystems ◽  
Natural Systems ◽  
Anaerobic Reactors ◽  
Rural And Urban ◽  
Pre Treatment

After the discovery of methane gas by Alessandro Volta in 1776, it took about 100 years before anaerobic processes for the treatment of wastewater and sludges were introduced. The development of high rate anaerobic digesters for the treatment of sewage and industrial wastewater took until the nineteen-seventies and for solid waste even till the nineteen-eighties. All digesters have in common that they apply natural anaerobic consortia of microorganisms for degradation and transformation processes. In view of this, it could be rewarding to evaluate the efficiency of natural ecosystems for their possible application. Examples of high rate anaerobic natural systems include the forestomach of ruminants and the hindgut of certain insects, such as termites and cockroaches. These “natural reactors” exhibit volumetric methane production rates as high as 35 l/l.d. The development of anaerobic reactors based on such natural anaerobic systems could produce eco-technologies for the effective management of a wide variety of solid wastes and industrial wastewater. Important limitations of anaerobic treatment of domestic sewage relate to the absence of nutrient and pathogen removal. A combination of anaerobic pre-treatment followed by photosynthetic post-treatment is proposed for the effective recovery of energy and nutrients from sewage. This eco-technology approach is based on the recognition that the main nutrient assimilating capacity is housed in photosynthetic plants. The proposed anaerobic-photosynthetic process is energy efficient, cost effective and applicable under a wide variety of rural and urban conditions. In conclusion: a natural systems approach towards waste management could generate affordable eco-technologies for effective treatment and resource recovery.

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