Rainfall index insurance for corn farmers in Shandong based on high-resolution weather and yield data

2017 ◽  
Vol 77 (2) ◽  
pp. 337-354 ◽  
Author(s):  
Wen Chen ◽  
Roman Hohl ◽  
Lee Kong Tiong
Keyword(s):  
High Resolution ◽  
Risk Premium ◽  
Phase Correlation ◽  
Production Costs ◽  
Drought Risk ◽  
Growth Phases ◽  
Yield Data ◽  
Basis Risk ◽  
Content Type ◽  
Rainfall Deficit

Purpose The purpose of this paper is to present the development of cumulative rainfall deficit (CRD) indices for corn in Shandong Province, China, based on high-resolution weather (county, 1980-2011) and yield data (township, 1989-2010) for five counties in Tai’an prefecture. Design/methodology/approach A survey with farming households is undertaken to obtain local corn prices and production costs to compute the sum insured. CRD indices are developed for five corn-growth phases. Rainfall is spatially interpolated to derive indices for areas that are outside a 25 km radius from weather stations. To lower basis risk, triggers and exits of the payout functions are statistically determined rather than relying on water requirement levels. Findings The results show that rainfall deficits in the main corn-growth phases explain yield reductions to a satisfying degree, except for the emergence phase. Correlation coefficients between payouts of the CRD indices and yield reductions reach 0.86-0.96 and underline the performance of the indices with low basis risk. The exception is SA-Xintai (correlation 0.71) where a total rainfall deficit index performs better (0.87). Risk premium rates range from 5.6 percent (Daiyue) to 12.2 percent (SA-Xintai) and adequately reflect the drought risk. Originality/value This paper suggests that rainfall deficit indices can be used in the future to complement existing indemnity-based insurance products that do not cover drought for corn in Shandong or for CRD indices to operate as a new insurance product.

High‐resolution velocity determination: Statistical phase correlation and image processing

Geophysics ◽  
1996 ◽  
Vol 61 (4) ◽  
pp. 1115-1127 ◽  
Author(s):  
Igor B. Morozov ◽  
Scott B. Smithson
Keyword(s):  
Image Processing ◽  
High Resolution ◽  
Phase Correlation ◽  
Statistical Hypothesis ◽  
Original Form ◽  
Velocity Spectrum ◽  
Statistical Hypothesis Testing ◽  
Simple Estimate ◽  
Optimal Velocity ◽  
Velocity Spectra

We address three areas of the problem of the stacking velocity determination: (1) the development of a new high‐resolution velocity determination technique, (2) the choice of an optimal velocity trial scenario, and (3) a unified approach to the comparison of time‐velocity spectra produced by various methods. We present a class of high‐resolution coherency measures providing five‐eight times better velocity resolution than conventional measures. The measure is based on the rigorous theory of statistical hypothesis testing and on the statistics of directional data. In its original form, our method analyzes only the phase distributions of the data, thus making unnecessary careful spherical divergence corrections and other normalization procedures. Besides the statistical one, we develop an “instantaneous” version of the conventional coherency measure. This measure is based on the concept of the trace envelope, thus eliminating the need for an averaging procedure. Finally, we design a hybrid high‐resolution coherency measure, incorporating the latter and the statistical one. Carrying out a systematic comparison of various measures of coherency, we present a simple estimate of an attainable velocity resolution. Based on this estimate, we define an optimal velocity grid, providing uniform coverage of all details of the time‐velocity spectrum. To facilitate quantitative comparisons of different coherency functions, we develop a unified normalization approach, based on techniques known in image processing. Described methods are tested on synthetic and field data. In both cases, we obtained a remarkable improvement in the time‐velocity resolution. The methods are general, very simple in implementation, and robust and reliable in application.

Tool workspace consideration for assembly plan generation

2021 ◽  
Vol 41 (5) ◽  
pp. 612-625
Author(s):  
Akram Bedeoui ◽  
Riadh Ben Hadj ◽  
Moncef Hammadi ◽  
Nizar Aifaoui
Keyword(s):  
Collision Detection ◽  
New Product ◽  
Production Costs ◽  
Assembly Sequence ◽  
Content Type ◽  
Plan Generation ◽  
Assembly Sequences ◽  
Dynamic Interference ◽  
Time Decrease

Purpose During the design of a new product, the generation of assembly sequences plans (ASPs) has become one of the most important problems taken into account by researchers. In fact, a good mounting order allows the time decrease of the assembly process which leads to the reduction of production costs. In this context, researchers developed several methods to generate and optimize ASP based on various criteria. Although this paper aims to improve the quality of ASP it is necessary to increase the number of criteria which must be taken into account when generating ASPs. Design/methodology/approach In this paper, an ASP generation approach, which is based on three main algorithms, is proposed. The first one generates a set of assembly sequences based on stability criteria. The obtained results are treated by the second algorithm which is based on assembly tools (ATs) workspace criterion. An illustrative example is used to explain the different steps of this proposed approach. Moreover, a comparative study is done to highlight its advantages. Findings The proposed algorithm verifies, for each assembly sequence, the minimal required workspace of used AT and eliminates the ASPs non-respecting this criterion. Finally, the remaining assembly sequences are treated by the third algorithm to reduce the AT change during the mounting operation. Originality/value The proposed approach introduces the concept of AT workspace to simulate and select ASPs that respect this criterion. The dynamic interference process allows the eventual collision detection between tool and component and avoids it. The proposed approach reduces the AT change during the mounting operations.

Overcoming basis risk in agricultural index insurance using crop simulation modeling and satellite crop phenology

2021 ◽  
Author(s):  
Mehdi H. Afshar ◽  
Timothy Foster ◽  
Thomas P. Higginbottom ◽  
Ben Parkes ◽  
Koen Hufkens ◽  
...  
Keyword(s):  
Smallholder Farmers ◽  
Simulation Models ◽  
Extreme Weather ◽  
Index Insurance ◽  
Yield Estimation ◽  
Crop Phenology ◽  
Yield Data ◽  
Basis Risk ◽  
Crop Simulation ◽  
Crop Simulation Models

<p>Extreme weather causes substantial damage to livelihoods of smallholder farmers globally and are projected to become more frequent in the coming decades as a result of climate change. Index insurance can theoretically help farmers to adapt and mitigate the risks posed by extreme weather events, providing a financial safety net in the event of crop damage or harvest failure. However, uptake of index insurance in practice has lagged far behind expectations. A key reason is that many existing index insurance products suffer from high levels of basis risk, where insurance payouts correlate poorly with actual crop losses due to deficiencies in the underlying index relationship, contract structure or data used to trigger insurance payouts to farmers. </p><p>In this study, we analyse to what extent the use of crop simulation models and crop phenology monitoring from satellite remote sensing can reduce basis risk in index insurance. Our approach uses a calibrated biophysical process-based crop model (APSIM) to generate a large synthetic crop yield training dataset in order to overcome lack of detailed in-situ observational yield datasets – a common limitation and source of uncertainty in traditional index insurance product design. We use this synthetic yield dataset to train a simple statistical model of crop yields as a function of meteorological and crop growth conditions that can be quantified using open-access earth observation imagery, radiative transfer models, and gridded weather products. Our approach thus provides a scalable tool for yield estimation in smallholder environments, which leverages multiple complementary sources of data that to date have largely been used in isolation in the design and implementation of index insurance</p><p>We apply our yield estimation framework to a case study of rice production in Odisha state in eastern India, an area where agriculture is exposed to significant production risks from monsoonal rainfall variability. Our results demonstrate that yield estimation accuracy improves when using meteorological and crop growth data in combination as predictors, and when accounting for the timing of critical crop development stages using satellite phenological monitoring. Validating against observed yield data from crop cutting experiments, our framework is able to explain around 54% of the variance in rice yields at the village cluster (Gram Panchayat) level that is the key spatial unit for area-yield index insurance products covering millions of smallholder farmers in India. Crucially, our modelling approach significantly outperforms vegetation index-based models that were trained directly on the observed yield data, highlighting the added value obtained from use of crop simulation models in combination with other data sources commonly used in index design.</p>

A framework for near real-time ROM stockpile modelling to improve blending efficiency

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shi Zhao ◽  
Tien-Fu Lu ◽  
Larissa Statsenko ◽  
Benjamin Koch ◽  
Chris Garcia
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Laser Scanning ◽  
High Efficiency ◽  
Reference Model ◽  
Geometric Model ◽  
Mining Industry ◽  
Management Systems ◽  
Content Type ◽  
Ore Grade

Purpose In the mining industry, a run-of-mine (ROM) stockpile is a temporary storage unit, but it is also widely accepted as an effective method to reduce the short-term variations of ore grade. However, tracing ore grade at ROM stockpiles accurately using most current fleet management systems is challenging, due to insufficient information available in real time. This study aims to build a three-dimensional (3D) model for ROM stockpiles continuously based on fine-grained grade information through integrating data from a number of ore grade tracking sources. Design/methodology/approach Following a literature review, a framework for a new stockpile management system is proposed. In this system, near real-time high-resolution 3D ROM stockpile models are created based on dump/load locations measured from global positioning system sensors. Each stockpile model contains a group of layers which are separated by different qualities. Findings Acquiring the geometric shapes of all the layers in a stockpile and cuts made by front wheel loaders provides a better understanding about the quality and quality distribution within a stockpile when it is stacked/reclaimed. Such a ROM stockpile model can provide information on predicating ore blend quality with high accuracy and high efficiency. Furthermore, a 3D stockyard model created based on such ROM stockpile models can help organisations optimise material flow and reduce the cost. Research limitations/implications The modelling algorithm is evaluated using a laboratory scaled stockpile at this stage. The authors expect to scan a real stockpile and create a reference model from it. Meanwhile, the geometric model cannot represent slump or collapse during reclaiming faithfully. Therefore, the model is expected to be reconcile monthly using laser scanning data. Practical implications The proposed model is currently translated to the operations at OZ Minerals. The use of such model will reduce the handling costs and improve the efficiency of existing grade management systems in the mining industry. Originality/value This study provides a solution to build a near real-time high-resolution multi-layered 3D stockpile model through using currently available information and resources. Such novel and low-cost stockpile model will improve the production rates with good output product quality control.

scholarly journals Development and Validation of a High-Resolution Melting Assay To Detect Azole Resistance in Aspergillus fumigatus

2017 ◽  
Vol 61 (12) ◽  
Author(s):  
L. Bernal-Martínez ◽  
H. Gil ◽  
O. Rivero-Menéndez ◽  
S. Gago ◽  
M. Cuenca-Estrella ◽  
...  
Keyword(s):  
High Resolution ◽  
Aspergillus Fumigatus ◽  
Tandem Repeats ◽  
High Resolution Melting ◽  
Screening Method ◽  
Melting Curve ◽  
Health Concern ◽  
Azole Resistance ◽  
Content Type ◽  
Selection Of

ABSTRACT The global emergence of azole-resistant Aspergillus fumigatus strains is a growing public health concern. Different patterns of azole resistance are linked to mutations in cyp51A. Therefore, accurate characterization of the mechanisms underlying azole resistance is critical to guide selection of the most appropriate antifungal agent for patients with aspergillosis. This study describes a new sequencing-free molecular screening tool for early detection of the most frequent mutations known to be associated with azole resistance in A. fumigatus. PCRs targeting cyp51A mutations at positions G54, Y121, G448, and M220 and targeting different tandem repeats (TRs) in the promoter region were designed. All PCRs were performed simultaneously, using the same cycling conditions. Amplicons were then distinguished using a high-resolution melting assay. For standardization, 30 well-characterized azole-resistant A. fumigatus strains were used, yielding melting curve clusters for different resistance mechanisms for each target and allowing detection of the most frequent azole resistance mutations, i.e., G54E, G54V, G54R, G54W, Y121F, M220V, M220I, M220T, M220K, and G448S, and the tandem repeats TR34, TR46, and TR53. Validation of the method was performed using a blind panel of 80 A. fumigatus azole-susceptible or azole-resistant strains. All strains included in the blind panel were properly classified as susceptible or resistant with the developed method. The implementation of this screening method can reduce the time needed for the detection of azole-resistant A. fumigatus isolates and therefore facilitate selection of the best antifungal therapy in patients with aspergillosis.

Impact of regulatory announcements on systemic risk in the Indian telecom sector

2018 ◽  
Vol 13 (5) ◽  
pp. 1395-1416 ◽  
Author(s):  
Sushma Priyadarsini Yalla ◽  
Som Sekhar Bhattacharyya ◽  
Karuna Jain
Keyword(s):  
Risk Premium ◽  
Systemic Risk ◽  
Service Providers ◽  
Policy Makers ◽  
Content Type ◽  
Risk Premiums ◽  
Buffering Hypothesis ◽  
Research Findings ◽  
Telecom Sector ◽  
The Impact

Purpose Post 1991, given the advent of liberalization and economic reforms, the Indian telecom sector witnessed a remarkable growth in terms of subscriber base and reduced competitive tariff among the service providers. The purpose of this paper is to estimate the impact of regulatory announcements on systemic risk among the Indian telecom firms. Design/methodology/approach This study employed a two-step methodology to measure the impact of regulatory announcements on systemic risk. In the first step, CAPM along with the Kalman filter was used to estimate the daily β (systemic risk). In the second step, event study methodology was used to assess the impact of regulatory announcements on daily β derived from the first step. Findings The results of this study indicate that regulatory announcements did impact systemic risk among telecom firms. The study also found that regulatory announcements either increased or decreased systemic risk, depending upon the type of regulatory announcements. Further, this study estimated the market-perceived regulatory risk premiums for individual telecom firms. Research limitations/implications The regulatory risk premium was either positive or negative, depending upon the different types of regulatory announcements for the telecom sector firms. Thus, this study contributes to the theory of literature by testing the buffering hypothesis in the context of Indian telecom firms. Practical implications The study findings will be useful for investors and policy-makers to estimate the regulatory risk premium as and when there is an anticipated regulatory announcement in the Indian telecom sector. Originality/value This is one of the first research studies in exploring regulatory risk among the Indian telecom firms. The research findings indicate that regulatory risk does exist in the telecom firms of India.

Production models of multiple products using a single machine under quality screening and reworking policies

2019 ◽  
Vol 14 (1) ◽  
pp. 232-259 ◽  
Author(s):  
Ata Allah Taleizadeh ◽  
Mahshid Yadegari ◽  
Shib Sankar Sana
Keyword(s):  
Single Machine ◽  
Manufacturing Systems ◽  
Production Systems ◽  
Production Costs ◽  
High Tech ◽  
Screening Process ◽  
Automatic Production ◽  
Content Type ◽  
Economic Production ◽  
Imperfect Items

Purpose The purpose of this study is to formulate two multi-product single-machine economic production quantity (EPQ) models by considering imperfect products. Two policies are assumed to deal with imperfect products: selling them at discount and applying a reworking process. Design/methodology/approach A screening process is used to identify imperfect items during and after production. Selling the imperfect items at a discount is examined in the first model and the reworking policy in the second model. In both models, demand during the production process is satisfied only by perfect items. Data collected from a case company are used to illustrate the performance of the two models. Moreover, a sensitivity analysis is carried out by varying the most important parameters of the models. Findings The case study in this research is used to demonstrate the applicability of the proposed models, i.e. the EPQ model with salvaging and reworking imperfect items. The models are applied to a high-tech un-plasticized polyvinyl chloride (UPVC) doors and windows manufacturer that produces different types of doors and windows. ROGAWIN Co. is a privately owned company that started in 2001 with fully automatic production lines. Finally, the results of applying the different ways of handling the imperfect items are discussed, along with managerial insights. Originality/value In real-world production systems, manufacturing imperfect products is unavoidable. That is why, it is important to make a proper decision about imperfect products to reduce overall production costs. Recently, applying a reworking strategy has gained the most interest when it comes to handling this problem. The principal idea of this research is to maximize the total profit of manufacturing systems by optimizing the period length under some capacity constraints. The proposed models were applied to a company of manufacturing UPVC doors and windows.

scholarly journals Economic questions of maize production on different soil types

2012 ◽  
pp. 289-292
Author(s):  
Dénes Sulyok
Keyword(s):  
Crop Protection ◽  
Conventional Tillage ◽  
Production Costs ◽  
Soil Types ◽  
Soil Protection ◽  
Yield Data ◽  
Maize Production ◽  
Chernozem Soils ◽  
Economical Aspect ◽  
Tillage Method

The requirements and objective of cultivation are in constant change. For example, different cultivation systems are developed for the purpose of soil protection, the preservation of its moisture content and on soils with various precipitation supply or production site conditions. Traditionally, one of the most important cultivation aims is crop needs. Further cost saving in fertilisation and crop protection can only be achieved by reducing the quality and quantity of production or it cannot be achieved at all. Furthermore, the costs can be significantly reduced by means of the rationalisation of cultivation. Energy and working time demand can also be notably reduced if ploughing is left out from the conventional tillage method. The key requirement of economicalness is to perform the cultivation at the optimal date, moisture level and the lowest possible cost.Within production costs, the cost of cultivation is between 3–17%, while they are between 8–36% within machinery costs. It is the vital condition the usability of each technological method to progressively reduce costs. Our evaluation work was carried out with the consideration of the yield data obtained from cooperating farms and the experiment database of the Institute for Land Utilisation, Regional Development and Technology of the Centre for Agricultural and Applied Economic Sciences of the University of Debrecen. Three technological methods (ploughing, heavy cultivator and loosening tillage) were used on several soil types which differ from in terms of cultivability (chernozem, sandy and sandy clay soils) from the economic/economical aspect. We examined the sectoral cost/income relation of maize production as an indicator plant. The maize price during the analytical period was 45 thousand HUF per t. On chernozem soils, the production of maize can be carried out on high income level, while maize production on sandy soils has a huge risk factor. The role of cultivation is the highest on high plasicity soils, since they have a huge energydemand and the there is a short amount of time available for each procedure in most cases.

scholarly journals Intra- and Interspecies Variability of Single-Cell Innate Fluorescence Signature of Microbial Cell

2019 ◽  
Vol 85 (18) ◽  
Author(s):  
Yutaka Yawata ◽  
Tatsunori Kiyokawa ◽  
Yuhki Kawamura ◽  
Tomohiro Hirayama ◽  
Kyosuke Takabe ◽  
...  
Keyword(s):  
Single Cell ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Population Level ◽  
Microbial Cell ◽  
Physiological Status ◽  
Growth Phases ◽  
Content Type ◽  
A Cell ◽  
Three Dimensional Space

ABSTRACT Here we analyzed the innate fluorescence signature of the single microbial cell, within both clonal and mixed populations of microorganisms. We found that even very similarly shaped cells differ noticeably in their autofluorescence features and that the innate fluorescence signatures change dynamically with growth phases. We demonstrated that machine learning models can be trained with a data set of single-cell innate fluorescence signatures to annotate cells according to their phenotypes and physiological status, for example, distinguishing a wild-type Aspergillus nidulans cell from its nitrogen metabolism mutant counterpart and log-phase cells from stationary-phase cells of Pseudomonas putida. We developed a minimally invasive method (confocal reflection microscopy-assisted single-cell innate fluorescence [CRIF] analysis) to optically extract and catalog the innate cellular fluorescence signatures of each of the individual live microbial cells in a three-dimensional space. This technique represents a step forward from traditional techniques which analyze the innate fluorescence signatures at the population level and necessitate a clonal culture. Since the fluorescence signature is an innate property of a cell, our technique allows the prediction of the types or physiological status of intact and tag-free single cells, within a cell population distributed in a three-dimensional space. Our study presents a blueprint for a streamlined cell analysis where one can directly assess the potential phenotype of each single cell in a heterogenous population by its autofluorescence signature under a microscope, without cell tagging. IMPORTANCE A cell’s innate fluorescence signature is an assemblage of fluorescence signals emitted by diverse biomolecules within a cell. It is known that the innate fluoresce signature reflects various cellular properties and physiological statuses; thus, they can serve as a rich source of information in cell characterization as well as cell identification. However, conventional techniques focus on the analysis of the innate fluorescence signatures at the population level but not at the single-cell level and thus necessitate a clonal culture. In the present study, we developed a technique to analyze the innate fluorescence signature of a single microbial cell. Using this novel method, we found that even very similarly shaped cells differ noticeably in their autofluorescence features, and the innate fluorescence signature changes dynamically with growth phases. We also demonstrated that the different cell types can be classified accurately within a mixed population under a microscope at the resolution of a single cell, depending solely on the innate fluorescence signature information. We suggest that single-cell autofluoresce signature analysis is a promising tool to directly assess the taxonomic or physiological heterogeneity within a microbial population, without cell tagging.

Evaluating effectiveness of rainfall index insurance

2018 ◽  
Vol 78 (5) ◽  
pp. 611-625 ◽  
Author(s):  
Rui Zhou ◽  
Johnny Siu-Hang Li ◽  
Jeffrey Pai
Keyword(s):  
Crop Yield ◽  
Variance Reduction ◽  
Index Insurance ◽  
Corn Yield ◽  
Basis Risk ◽  
Content Type ◽  
Optimal Insurance ◽  
Rainfall Index ◽  
Temperature And Precipitation ◽  
Insurance Portfolio

Purpose The purpose of this paper is to examine the reduction of crop yield uncertainty using rainfall index insurances. The insurance payouts are determined by a transparent rainfall index rather than actual crop yield of any producer, thereby circumventing problems of adverse selection and moral hazard. The authors consider insurances on rainfall indexes of various months and derive an optimal insurance portfolio that minimizes the income variance for a crop producer. Design/methodology/approach Various regression models are considered to relate crop yield to monthly mean temperature and monthly cumulative precipitation. A bootstrapping method is used to simulate weather indexes and corn yield in a future year with the correlation between precipitation and temperature incorporated. Based on the simulated scenarios, the optimal insurance portfolio that minimizes the income variance for a crop producer is obtained. In addition, the impact of correlation between temperature and precipitation, availability of temperature index insurance and geographical basis risk on the effectiveness of rainfall index insurance is examined. Findings The authors illustrate the approach with the corn yield in Illinois east crop reporting district and weather data of a city in the same district. The analysis shows that corn yield in this district is negatively influenced by excessive precipitation in May and drought in June–August. Rainfall index insurance portfolio can reduce the income variance by up to 51.84 percent. Failing to incorporate the correlation between temperature and precipitation decreases variance reduction by 11.6 percent. The presence of geographical basis risk decreases variance reduction by a striking 24.11 percent. Allowing for the purchase of both rainfall and temperature index insurances increases variance reduction by 13.67 percent. Originality/value By including precipitation shortfall into explanatory variables, the extended crop yield model explains more fluctuation in crop yield than existing models. The authors use a bootstrapping method instead of complex parametric models to simulate weather indexes and crop yield for a future year and assess the effectiveness of rainfall index insurance. The optimal insurance portfolio obtained provides insights on the practical development of rainfall insurance for corn producers, from the selection of triggering index to the demand of the insurance.

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