scholarly journals A Reference Standard Process Model for Agriculture to Facilitate Efficient Implementation and Adoption of Precision Agriculture

Agriculture ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1257
Author(s):  
Rok Rupnik ◽  
Damjan Vavpotič ◽  
Jurij Jaklič ◽  
Aleš Kuhar ◽  
Miroslav Plavšić ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Mobile Applications ◽  
Delphi Technique ◽  
Process Model ◽  
Large Scale ◽  
Reference Standard ◽  
Standard Process ◽  
Software Companies ◽  
Study Results ◽  
Funded Project

Agriculture is a sector that today demands even greater efficiency; thus, it relies extensively on the use of precision agriculture technologies: IoT systems, mobile applications, and other digitalization technologies. Experience from a large-scale EU-funded project with a consortium made up of several software companies shows that software companies have a different and unequal knowledge/understanding of agricultural processes and the use of precision agriculture in agricultural processes. This finding coupled with what is known about the standard process model for IT governance (COBIT) triggered the idea of a reference standard process model for agriculture (RSPMA), which we present in this paper. We applied the Delphi technique to assess the RSPMA and evaluate its potential implementation in the area of agriculture. A panel of 20 members from Slovenia, Romania, Croatia, and Serbia was established for the study. The majority of RSPMA elements were identified as appropriate for the use in agriculture by the panel. The study results show that RSPMA is suitable for use in this field.

scholarly journals Mode-Based Analysis and Optimal Operation of MSF Desalination System

Processes ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 794
Author(s):  
Hanhan Gao ◽  
Aipeng Jiang ◽  
Qiuyun Huang ◽  
Yudong Xia ◽  
Farong Gao ◽  
...  
Keyword(s):  
Process Model ◽  
Large Scale ◽  
Optimal Operation ◽  
Production Performance ◽  
Operational Cost ◽  
Steam Temperature ◽  
Operational Parameters ◽  
Whole Process ◽  
Multi Stage ◽  
Study Results

Multi-stage flash (MSF) desalination plays an important role in achieving large-scale fresh water driven by thermal energy. In this paper, based on first-principle modeling of a typical multi-stage flash desalination system, the effects of different operational parameters on system performance and operational optimization for cost saving were extensively studied. Firstly, the modelled desalination system was divided into flash chamber modules, brine heater modules, mixed modules and split modules, and based on energy and mass conservation laws the equations were formulated and put together to describe the whole process model. Then, with physical parameter calculation the whole process was simulated and analyzed on the platform of MATLAB, and the water production performance effected by operational parameters such as the feed temperature of seawater, the recycle brine from the discharge section, steam temperature and flowrate of recycled brine were discussed and analyzed. Then, the optimal operation to achieve maximize GOR (gained output ratio) with fixed freshwater demand was considered and performed, and thus the optimal flowrate of recycled brine, steam temperature, and seawater output flowrate from rejection section were obtained based on the established model. Finally, considering that minimizing the daily operational cost is a more rational objective, the operational cost equations were formulated and the optimal problem to minimize the daily operational cost was solved and the optimal manipulated variables at different hours were obtained. The study results can be used for guideline of real time optimization of the MSF system.

scholarly journals Precision Agriculture for Resource Use Efficiency in Smallholder Farming Systems in Sub-Saharan Africa: A Systematic Review

2021 ◽  
Vol 13 (3) ◽  
pp. 1158
Author(s):  
Cecilia M. Onyango ◽  
Justine M. Nyaga ◽  
Johanna Wetterlind ◽  
Mats Söderström ◽  
Kristin Piikki
Keyword(s):  
Resource Use ◽  
Precision Agriculture ◽  
Large Scale ◽  
English Language ◽  
Management Practices ◽  
Smallholder Farmers ◽  
Management Strategies ◽  
Sub Saharan Africa ◽  
Smallholder Farming ◽  
Sub Saharan

Opportunities exist for adoption of precision agriculture technologies in all parts of the world. The form of precision agriculture may vary from region to region depending on technologies available, knowledge levels and mindsets. The current review examined research articles in the English language on precision agriculture practices for increased productivity among smallholder farmers in Sub-Saharan Africa. A total of 7715 articles were retrieved and after screening 128 were reviewed. The results indicate that a number of precision agriculture technologies have been tested under SSA conditions and show promising results. The most promising precision agriculture technologies identified were the use of soil and plant sensors for nutrient and water management, as well as use of satellite imagery, GIS and crop-soil simulation models for site-specific management. These technologies have been shown to be crucial in attainment of appropriate management strategies in terms of efficiency and effectiveness of resource use in SSA. These technologies are important in supporting sustainable agricultural development. Most of these technologies are, however, at the experimental stage, with only South Africa having applied them mainly in large-scale commercial farms. It is concluded that increased precision in input and management practices among SSA smallholder farmers can significantly improve productivity even without extra use of inputs.

scholarly journals Evaluating Machine Learning and Geostatistical Methods for Spatial Gap-filling of Monthly ESA CCI Soil Moisture in China

2021 ◽  
Vol 13 (14) ◽  
pp. 2848
Author(s):  
Hao Sun ◽  
Qian Xu
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Water Resource Management ◽  
Large Scale ◽  
Gap Filling ◽  
Spatial Continuity ◽  
Study Results ◽  
Data Gaps

Obtaining large-scale, long-term, and spatial continuous soil moisture (SM) data is crucial for climate change, hydrology, and water resource management, etc. ESA CCI SM is such a large-scale and long-term SM (longer than 40 years until now). However, there exist data gaps, especially for the area of China, due to the limitations in remote sensing of SM such as complex topography, human-induced radio frequency interference (RFI), and vegetation disturbances, etc. The data gaps make the CCI SM data cannot achieve spatial continuity, which entails the study of gap-filling methods. In order to develop suitable methods to fill the gaps of CCI SM in the whole area of China, we compared typical Machine Learning (ML) methods, including Random Forest method (RF), Feedforward Neural Network method (FNN), and Generalized Linear Model (GLM) with a geostatistical method, i.e., Ordinary Kriging (OK) in this study. More than 30 years of passive–active combined CCI SM from 1982 to 2018 and other biophysical variables such as Normalized Difference Vegetation Index (NDVI), precipitation, air temperature, Digital Elevation Model (DEM), soil type, and in situ SM from International Soil Moisture Network (ISMN) were utilized in this study. Results indicated that: 1) the data gap of CCI SM is frequent in China, which is found not only in cold seasons and areas but also in warm seasons and areas. The ratio of gap pixel numbers to the whole pixel numbers can be greater than 80%, and its average is around 40%. 2) ML methods can fill the gaps of CCI SM all up. Among the ML methods, RF had the best performance in fitting the relationship between CCI SM and biophysical variables. 3) Over simulated gap areas, RF had a comparable performance with OK, and they outperformed the FNN and GLM methods greatly. 4) Over in situ SM networks, RF achieved better performance than the OK method. 5) We also explored various strategies for gap-filling CCI SM. Results demonstrated that the strategy of constructing a monthly model with one RF for simulating monthly average SM and another RF for simulating monthly SM disturbance achieved the best performance. Such strategy combining with the ML method such as the RF is suggested in this study for filling the gaps of CCI SM in China.

Bayesian active learning of interatomic force field for molecular dynamics simulation of Pt/Ag(111)

2021 ◽  
Author(s):  
Kai Xu ◽  
Lei Yan ◽  
Bingran You
Keyword(s):  
Molecular Dynamics ◽  
Active Learning ◽  
Force Field ◽  
Density Functional ◽  
Process Model ◽  
Large Scale ◽  
Computational Cost ◽  
Dynamics Simulation ◽  
Potential Energy Landscape ◽  
Three Body

Force field is a central requirement in molecular dynamics (MD) simulation for accurate description of the potential energy landscape and the time evolution of individual atomic motions. Most energy models are limited by a fundamental tradeoff between accuracy and speed. Although ab initio MD based on density functional theory (DFT) has high accuracy, its high computational cost prevents its use for large-scale and long-timescale simulations. Here, we use Bayesian active learning to construct a Gaussian process model of interatomic forces to describe Pt deposited on Ag(111). An accurate model is obtained within one day of wall time after selecting only 126 atomic environments based on two- and three-body interactions, providing mean absolute errors of 52 and 142 meV/Å for Ag and Pt, respectively. Our work highlights automated and minimalistic training of machine-learning force fields with high fidelity to DFT, which would enable large-scale and long-timescale simulations of alloy surfaces at first-principles accuracy.

Specificity of using messengers by schoolchildren and students in mobile learning

Ergodesign ◽  
2021 ◽  
Vol 0 (3) ◽  
pp. 197-204
Author(s):  
Pavel Paderno ◽  
Elizaveta Stroeva
Keyword(s):  
High School ◽  
High School Students ◽  
Mobile Applications ◽  
Online Survey ◽  
Online Communication ◽  
School Students ◽  
Study Results ◽  
The Russian Federation ◽  
Goals And Objectives ◽  
Positive Effect

The aim of the work is to identify the functionality required by mobile messengers for convenient online communication between pupils and high school students. To achieve this aim, a survey of 116 questions was developed, which adjusted to the respondent’s answers and reduced its volume in order to avoid the respondents’ fatigue and to decrease the time spent on completing the survey. An online survey of students aged 16 to 24 living in different cities of the Russian Federation was carried out. Then the information obtained was processed, and possible relations between the analysis results were found. Based on the study results, recommendations were formed to improve messengers according to the students- users’ goals and objectives. Now messengers are created mainly for the widespread use. There are already more than a hundred of them, and therefore products need to stand out in order to be competitive. One of the ways to excel is to be narrowly focused, tailored to a specific audience. Since the functionality of the messenger directly affects its popularity, the introduction and refinement of the necessary functions will have a positive effect on the number of users. The analysis shows that developers of instant messengers can improve the efficiency of using messengers by the students and, possibly, reduce the number of installed mobile applications on their devices, and, consequently, decrease the number of competitors for their target audience.

Public services: a standard process model following a structured process redesign

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kamal K. Mukherjee ◽  
Laura Reka ◽  
Rudina Mullahi ◽  
Keldi Jani ◽  
Jonida Taraj
Keyword(s):  
Business Process ◽  
Public Service ◽  
Process Model ◽  
Public Services ◽  
Case Study Research ◽  
Standard Process ◽  
Content Type ◽  
Process Redesign ◽  
Resource Reuse ◽  
The Government

PurposeDespite widespread adoption of business process reengineering (BPR) for better delivery efficiency of public services, a structured approach continues to elude the most value-adding phase of BPR: business process redesign. From another viewpoint, the rising currency of Whole-of-Government (WoG) and “shared services” initiatives signal an unmissable trend toward resource reuse across public service agencies (PSAs) through business process standardization (BPS). This research invokes BPS into process redesign to produce a process redesign framework (PRF) and deploys the same to build a standard process model (SPM) for services of the government of Albania (GoA).Design/methodology/approachThe methodology follows the design science research (DSR) paradigm, wherein best practices extracted from literature are synthesized with stakeholder inputs to design the PRF and SPM, both of which are then evaluated with case study research.FindingsAdoption of PRF/SPM on a WoG basis will not only reduce service lead time but also enable a variety of public services to share the same process, thereby further saving costs for GoA. The research outputs will accelerate reengineering and subsequent digitalization of public service operations.Research limitations/implicationsImplementing SPM will maximize resource reuse and help offer uniform and integrated public services to GoA's customers. It will also enable demand-driven staff mobilization across GoA agencies. The proposed PRF/SPM have limitations in that they consider only flow aspects of service processes with aspects of conversion being ignored.Originality/valueThis research fulfills the need for a systematic approach to process redesign and prepares GoA for a WoG treatment to its BPR efforts.

scholarly journals Real-Time Safety Evaluation for Slope during Construction Using Numerical Forecast and Sensor Monitoring Platform

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2978 ◽  
Author(s):  
Sherong Zhang ◽  
Dejun Hou ◽  
Chao Wang ◽  
Xuexing Cao ◽  
Fenghua Zhang ◽  
...  
Keyword(s):  
Numerical Model ◽  
Real Time ◽  
Evaluation System ◽  
Large Scale ◽  
Safety Evaluation ◽  
The Real ◽  
Study Results ◽  
Data Feedback ◽  
Numerical Forecast ◽  
Slope Safety

Geology uncertainties and real-time construction modification induce an increase of construction risk for large-scale slope in hydraulic engineering. However, the real-time evaluation of slope safety during construction is still an unsettled issue for mapping large-scale slope hazards. In this study, the real-time safety evaluation method is proposed coupling a construction progress with numerical analysis of slope safety. New revealed geological information, excavation progress adjustment, and the support structures modification are updating into the slope safety information model-by-model restructuring. A dynamic connection mapping method between the slope restructuring model and the computable numerical model is illustrated. The numerical model can be generated rapidly and automatically in database. A real-time slope safety evaluation system is developed and its establishing method, prominent features, and application results are briefly introduced in this paper. In our system, the interpretation of potential slope risk is conducted coupling dynamic numerical forecast and monitoring data feedback. The real case study results in a comprehensive real-time safety evaluation application for large slope that illustrates the change of environmental factor and construction state over time.

scholarly journals Evapotranspiration Estimation with Small UAVs in Precision Agriculture

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6427
Author(s):  
Haoyu Niu ◽  
Derek Hollenbeck ◽  
Tiebiao Zhao ◽  
Dong Wang ◽  
YangQuan Chen
Keyword(s):  
Energy Balance ◽  
High Resolution ◽  
Spatial Resolution ◽  
Precision Agriculture ◽  
Large Scale ◽  
Bowen Ratio ◽  
Future Research ◽  
Accurate Estimation ◽  
Research Areas ◽  
Energy Balance Approach

Estimating evapotranspiration (ET) has been one of the most critical research areas in agriculture because of water scarcity, the growing population, and climate change. The accurate estimation and mapping of ET are necessary for crop water management. Traditionally, researchers use water balance, soil moisture, weighing lysimeters, or an energy balance approach, such as Bowen ratio or eddy covariance towers to estimate ET. However, these ET methods are point-specific or area-weighted measurements and cannot be extended to a large scale. With the advent of satellite technology, remote sensing images became able to provide spatially distributed measurements. However, the spatial resolution of multispectral satellite images is in the range of meters, tens of meters, or hundreds of meters, which is often not enough for crops with clumped canopy structures, such as trees and vines. Unmanned aerial vehicles (UAVs) can mitigate these spatial and temporal limitations. Lightweight cameras and sensors can be mounted on the UAVs and take high-resolution images. Unlike satellite imagery, the spatial resolution of the UAV images can be at the centimeter-level. UAVs can also fly on-demand, which provides high temporal imagery. In this study, the authors examined different UAV-based approaches of ET estimation at first. Models and algorithms, such as mapping evapotranspiration at high resolution with internalized calibration (METRIC), the two-source energy balance (TSEB) model, and machine learning (ML) are analyzed and discussed herein. Second, challenges and opportunities for UAVs in ET estimation are also discussed, such as uncooled thermal camera calibration, UAV image collection, and image processing. Then, the authors share views on ET estimation with UAVs for future research and draw conclusive remarks.

scholarly journals The Relationships between Total Protein Intake, Protein Sources, Physical Activity, and Lean Mass in a Representative Sample of the US Adults

Nutrients ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 3151
Author(s):  
Furong Xu ◽  
Jacob E. Earp ◽  
Maya Vadiveloo ◽  
Alessandra Adami ◽  
Matthew J. Delmonico ◽  
...  
Keyword(s):  
Physical Activity ◽  
Lean Mass ◽  
Total Protein ◽  
Representative Sample ◽  
Protein Intake ◽  
Large Scale ◽  
Weight Status ◽  
Protein Sources ◽  
Total Protein Intake ◽  
Study Results

Background: Although dietary protein and physical activity play essential roles in developing and preserving lean mass, studies exploring these relationships are inconsistent, and large-scale studies on sources of protein and lean mass are lacking. Accordingly, the present study examined the relationship between total protein intake, protein sources, physical activity, and lean mass in a representative sample of US adults. Methods: This cross-sectional study analyzed data from 2011–2016 US National Health and Nutrition Examination Survey and corresponding Food Patterns Equivalents Database (n = 7547). Multiple linear regression models were performed to examine the sex-specific associations between total protein intake, protein sources (Dairy, Total Protein Foods, Seafood, and Plant Proteins), physical activity, and lean mass adjusting for demographics, weight status, and total daily energy intake. Results: Total protein intake was inversely related to lean mass in females only (Lean mass index: β= −0.84, 95%CI: −1.06–−0.62; Appendicular lean mass index: β= −0.35, 95%CI: −0.48–−0.22). However, protein sources and physical activity was positively associated with lean mass in males and/or females (p < 0.05). Conclusion. Study results suggest that consuming more protein daily had a detrimental influence on lean mass in females whereas eating high-quality sources of proteins and being physically active are important for lean mass for men and women. However, the importance of specific protein sources appears to differ by sex and warrants further investigation.

scholarly journals Impact study of NOOR 1 project on the Moroccan territorial economic development

2021 ◽  
Vol 6 ◽  
pp. 8
Author(s):  
Amale Laaroussi ◽  
Abdelghrani Bouayad ◽  
Zakaria Lissaneddine ◽  
Lalla Amina Alaoui
Keyword(s):  
Economic Development ◽  
Renewable Energy ◽  
Economic Impact ◽  
Large Scale ◽  
Solar Power ◽  
Local Level ◽  
Concentrated Solar Power ◽  
Professional Literature ◽  
Study Results ◽  
The Impact

Morocco is one of the countries investing more and more in Renewable Energy (RE) technologies to meet the growing demand for energy and ensure the security of supply in this sector. The number of solar projects planned and implemented, as well as solar thermal projects in the form of Concentrating Solar Power (CSP) installations is steadily increasing. Many of these installations are designed as large utility systems. In order to provide strong evidence on local, regional and even national impacts, this article examines the impacts of large-scale renewable energy projects on territorial development, based on a case study of the NOOR 1 (Concentrated Solar Power (CSP)) project in Ouarzazate, Morocco. The data collected during this study, conducted through semi-structured interviews with experts, stakeholders, local community representatives and combined with an analysis of documents provided by the NOOR 1 project managers, investors and consulting firms specialized in the field of Renewable Energy, provide detailed evidence on the type and magnitude of impacts on the economic development of the Moroccan southern region where the NOOR 1 plant is located. The data collected is analyzed using NVIVO software. The study results in a consolidated list of many impacts with varying levels of significance for different stakeholder groups, including farmers, youth, women, community representatives and small and medium firms owners. It should be noted that the importance of analyzing the economic impact of large infrastructure projects is widely recognized, but so far, there is little published in the academic and professional literature on the potential impacts of these projects at the local level. Even less information is available on the local impacts of large-scale project implementation in Morocco. While many macroeconomic studies have fed the recent surge in investment in RE projects with the promise of multiple social, economic, environmental, and even geopolitical benefits at the macro level, public debates and discussions have raised considerable doubts. The question of whether these promises would also leave their marks at the local level has also arisen. Despite these uncertainties, very few academics and practitioners have conducted research to empirically develop a good understanding of the impact of RE projects at the local level. To fill this research gap, the economic impact analysis of NOOR 1 provides a detailed empirical overview, which allows a better understanding of the effects that the infrastructure developments of Concentrated Solar Power (CSP) plants can have on the economic environment in which they are located.

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