Characterization and Combination of Agronomical Entities in Accordance with Spatial and Quantitative Imprecision

Author(s):  
Karima Zayrit ◽  
Eric Desjardin ◽  
Cyril de Runz ◽  
Herman Akdag

One of the objectives of the authors' studies on the monitoring of agricultural practices is to deal with imperfect spatial and quantitative information, and to always associate a quality evaluation with acquired or computed data from each location in the territory being studied. In order to produce quantitative information for each location and to consider the imprecision of data, this paper introduces the notion of fuzzy agronomical entities that consider both fuzzy spatial and quantitative information. Then, it proposes a new approach for propagating spatial imprecision to fuzzy quantitative values using two fuzzy combination operators. This method produces the fuzzy quantity of spatially disseminated chemicals for each location.

Author(s):  
Elvira Immacolata Locuratolo

The article is concerned with the proposal of a new approach of conceptual database design, called evolving conceptual database design, which exploits the structure for the preservation of database classes/concepts within the design. In order to discuss the opportunity to take into consideration this approach, the structure is constructed starting from a database conceptual graph. The leaves of the structure are mapped to a logical/object database graph. Horizontal steps of constructive logical database design extend the model. The computational costs required to design the structure for the preservation of database classes/concepts, as well as the qualitative/conceptual costs of the logical models resulting from the constructive design, are discussed.


2014 ◽  
Vol 73 (AoP) ◽  
Author(s):  
Lorenzo Traversetti ◽  
Simona Ceschin ◽  
Alessandro Manfrin ◽  
Massimiliano Scalici

2014 ◽  
Vol 31 (2) ◽  
pp. 231-249 ◽  
Author(s):  
Yen-Ching Chang ◽  
Chun-Ming Chang ◽  
Liang-Hwa Chen ◽  
Tung-Jung Chan

Purpose – Assessing image quality is a difficult task. Different demands need distinct criteria, so it is not realistic to decide which contrast enhancement method is better only through one criterion. The main purpose is to propose an efficient scheme to effectively evaluate image quality. Furthermore, the idea can be applied in other fields. Design/methodology/approach – To objectively and quantitatively assess image quality, the authors integrate four criteria into one composite criterion and use it to evaluate seven existing contrast enhancement methods. The mechanism of integration is through a newly proposed way of computing a grey relational grade (GRGd), called the consistent grey relational grade (CGRGd). Findings – In this paper, the authors propose the CGRGd, which is more efficient and consistent than other existing GRGds. When applied to image quality evaluation, the proposed CGRGd can effectively choose the best method than others. The results also indicate that the proposed CGRGd combined with appropriate criteria can be widely used in the field of multiple criteria. Originality/value – The proposed CGRGd is a new approach to the problem of multi-criteria evaluation, and its application to the evaluation of image quality is a novel idea. For readers interested in the field of multi-criteria decision-making, the CGRGd provides an efficient and effective alternative.


2016 ◽  
Vol 20 (2) ◽  
pp. 743-752 ◽  
Author(s):  
Vladimir Milisavljevic ◽  
Dragan Medenica ◽  
Vojin Cokorilo ◽  
Ivica Ristovic

2021 ◽  
Author(s):  
Mauro De Feudis ◽  
Gloria Falsone ◽  
Gian Marco Salani ◽  
Enrico Mistri ◽  
Valentina Brombin ◽  
...  

<p>Soil organic carbon (SOC) content is the major indicator used for soil quality evaluation because provides several ecosystem functions. However, SOC content does not allow to understand the soil potential to deliver the key ecosystem functions because most of soil processes are linked to soil biota. This research aimed to demonstrate the importance of soil indicators related to the SOC cycle rather than SOC content for soil quality evaluation. To reach this goal, three farms characterized by diverse soil types (Fluvisol and Cambisol) were selected in the Po plain of Emilia-Romagna Region, Italy. Moreover, different agricultural practices were performed: three-year-old pear trees using conventional management for Maccanti farm (MAC), 10-year pear orchard with integrated management for Zani (ZAN) and 10-year peach orchard with organic management for Biondi (BIO). MAC is located in ancient reclamation area, where Fluvisols are enriched of peat and organic matter. In each farm, soil samples from 0–15 (hereafter called topsoil) and 15–30 cm (hereafter called subsoil) depth were collected and analysed for the contents of SOC, labile organic carbon (Clab), fulvic acids, humic acids, humin and microbial biomass–C (Cmic), and for microbial respiration (Resp). In order to evaluate the soil processes related to C cycle, the humification rate (HR), metabolic quotient (qMET) and microbial quotient (qMIC) were calculated. MAC soil showed the highest SOC content without differences between topsoil and subsoil, due to ancient reclamation and agricultural management. BIO and ZAN showed similar SOC contents and it was higher in the topsoil than in subsoil due to grassy turf. Compared to BIO and ZAN, MAC soil showed a higher amount of Clab, and SOC was composed by a lower percentage of stable organic carbon (humin). Despite the higher Clab concentration, which is an easily available C source for microbes, no differences of Resp were observed among the sites, and MAC showed the lowest Cmic content. These data would indicate the presence in MAC of stress conditions which do not allow the growth of microbial biomass. The occurrence of stress conditions is clearly showed by the lowest qMET indicating how the conventional agricultural practices in peaty Fluvisol negatively affect the carbon use efficiency of microbial biomass. As a consequence, these stress conditions do not allow the C stabilization as suggested by the lowest qMIC. Further, the low C stabilization processes are highlighted by the highest HR. Conversely, despite the lowest content of Clab, BIO soil showed the lowest qMET and the highest qMIC suggesting how organic managements tend to improve the soil quality. Hence, the present study highlighted the importance of indicators linked to soil microbiome for soil quality evaluation in order to preserve its ecosystem functions. Indeed, organic carbon rich soils as those of MAC would indicate high quality soils but, because of the highly impacting practices, they showed stress conditions when the indicators linked to soil microbiome are taken in account. Therefore, if these indicators are not considered for soil quality evaluation, several fields used for agricultural purposes could become degraded.</p>


2019 ◽  
Vol 109 (10) ◽  
pp. 722-726
Author(s):  
M. Liewald ◽  
P. Essig ◽  
C. Bolay

Steigende Anforderungen an die Qualität von Außenhautteilen stellen Unternehmen in der Automobilindustrie vor neue Herausforderungen. Eine wichtige Rolle spielt dabei der Werkzeugentstehungsprozess, der von zeitintensiven Schleifarbeiten geprägt ist. Der Beitrag zeigt einen neuartigen Ansatz zur Datenrückführung von Traganteilen bestimmter Wirkflächenzonen in die Umformsimulation durch optische Messtechnik. Damit kann der aktuelle Tryout-Zustand mit der Simulation verglichen werden.   Increasing demands on the quality of outer car panels pose new challenges for manufacturing companies in the automotive industry. The tryout process of dies needs special consideration as it is characterized by time-consuming manual grinding operations. This paper focusses on a new approach for data feedback of contact areas into forming simulation by optical measurement technology. This allows for comparing the current tryout state with the forming simulation.


2018 ◽  
Vol 31 (1) ◽  
pp. 1418-1436 ◽  
Author(s):  
Gina Ionela Butnaru ◽  
Amanda Miller ◽  
Valentin Nita ◽  
Mirela Stefanica

2017 ◽  
Vol 18 (2) ◽  
pp. 723-736 ◽  
Author(s):  
Jingneng Ni ◽  
Jiuping Xu ◽  
Mengxiang Zhang

Abstract Water quality evaluation is a key task in water resource management and pollution control. Current evaluation methods are rooted in water quality index, which assesses the water quality based on the exact concentration of various pollutants. However, the interaction between the pollutants and the water environment should also be considered. This paper suggests a new approach, which integrates pollutant interaction with water environment and parameter uncertainty to water quality evaluation. The new approach is compared with traditional methods. Then, an inexact evaluation model, the integrated water quality evaluation model under uncertainty, is established in accordance with the proposed approach, in which catastrophe theory is used to deal with the ambiguous internal mechanism of the interaction between the pollutants and the water environment. As there are significant uncertainties in water quality evaluations, fuzzy random variables are employed to describe the inexact monitoring data. To solve the proposed model, a new algorithm is designed. The model is then applied to an actual case: Lake Chaohu, China. The results are compared between the proposed method and China's current evaluation method (i.e. max-index method). Some brief analysis and discussion are given about the results, which could be helpful in guiding environmental management decision-making.


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