scholarly journals Method of Spare Parts Prediction Models Evaluation Based on Grey Comprehensive Correlation Degree and Association Rules Mining: A Case Study in Aviation

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Jun Wang ◽  
Xing Pan ◽  
Ligeng Wang ◽  
Wei Wei
Keyword(s):  
Association Rules ◽  
Prediction Models ◽  
Spare Parts ◽  
Normal Operation ◽  
Inventory Cost ◽  
Association Rules Mining ◽  
Correlation Degree ◽  
Different Types ◽  
Airline Company

Probability of spare parts sufficiency is crucial in the process of the normal operation of businesses, especially for the airline company. However, higher support sufficiency could inevitably lead to the increase of inventory cost of spare parts and restrict a company’s efficiency. Therefore, it is important for businesses to reduce material cost on the premise of normal operation in order to accurately predict spare parts requirements based on reasonable models. The purpose of this paper is to solve problems with the evaluation of spare parts prediction models and to improve efficiency of company. Firstly, this paper summarizes a series of prediction models of spare parts requirements and applies the grey comprehensive correlation degree to rank the models. Secondly, the method of association rules mining is used to discover the association relationships between the types of spare parts and the prediction models. Finally, a case study in aviation is given to demonstrate the feasibility of the methodology, and optimal prediction models are recommended for aircraft spare parts. In accordance with the association relationships, the applicable prediction model can be provided in terms of different types of spare parts. This model will greatly enhance the work efficiency of spare parts prediction and improve the prediction tasks for the aircraft companies.

Detecting Electronic Initiators Using Electromagnetic Emissions

2014 ◽  
pp. 69-99
Author(s):  
Colin Stagner ◽  
Sarah Seguin ◽  
Steve Grant ◽  
Daryl Beetner
Keyword(s):  
Low Power ◽  
Normal Operation ◽  
Radio Receivers ◽  
Novel Technique ◽  
Different Types ◽  
Radio Signals ◽  
Electromagnetic Emissions ◽  
Weak Stimulation ◽  
Explosive Device

The accurate and timely discovery of radio receivers can assist in the detection of radio-controlled explosives. By detecting radio receivers, it is possible to indirectly infer the presence of an explosive device. Radio receivers unintentionally emit low-power radio signals during normal operation. By using a weak stimulation signal, it is possible to inject a known signal into these unintended emissions. This process is known as stimulated emissions. Unlike chemical traces, these stimulated emissions can propagate through walls and air-tight containers. The following case study discusses methods for detecting and locating two different types of radio receivers. Functional stimulated emissions detectors are constructed, and their performance is analyzed. Stimulated emissions are capable of detecting super-regenerative receivers at distances of at least one hundred meters and accurately locating superheterodyne receivers at distances of at least fifty meters. These results demonstrate a novel technique for detecting potential explosive threats at stand-off detection distances.

Different Types of Association Rules Mining Review

2012 ◽  
Vol 241-244 ◽  
pp. 1589-1592
Author(s):  
Jun Tan
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
Rule Mining ◽  
Association Rules Mining ◽  
Fuzzy Association Rules ◽  
Weighted Association Rules ◽  
Application Systems ◽  
Different Types ◽  
Multi Level

In recent years, many application systems have generate large quantities of data, so it is no longer practical to rely on traditional database technique to analyze these data. Data mining offers tools for extracting knowledge from data, leading to significant improvement in the decision-making process. Association rules mining is one of the most important data mining technology. The paper first presents the basic concept of association rule mining, then discuss a few different types of association rules mining including multi-level association rules, multidimensional association rules, weighted association rules, multi-relational association rules, fuzzy association rules.

Participatory Mapping in Browns Canyon National Monument, Colorado (USA)

2017 ◽  
Vol 1 (1) ◽  
pp. 1-16
Author(s):  
John Harner ◽  
Lee Cerveny ◽  
Rebecca Gronewold
Keyword(s):  
Land Management ◽  
Planning Process ◽  
Management Plan ◽  
Bureau Of Land Management ◽  
National Monument ◽  
Resource Managers ◽  
Different Types ◽  
Us Forest Service ◽  
Natural Resource Managers

Natural resource managers need up-to-date information about how people interact with public lands and the meanings these places hold for use in planning and decision-making. This case study explains the use of public participatory Geographic Information System (GIS) to generate and analyze spatial patterns of the uses and values people hold for the Browns Canyon National Monument in Colorado. Participants drew on maps and answered questions at both live community meetings and online sessions to develop a series of maps showing detailed responses to different types of resource uses and landscape values. Results can be disaggregated by interaction types, different meaningful values, respondent characteristics, seasonality, or frequency of visit. The study was a test for the Bureau of Land Management and US Forest Service, who jointly manage the monument as they prepare their land management plan. If the information generated is as helpful throughout the entire planning process as initial responses seem, this protocol could become a component of the Bureau’s planning tool kit.

Effective Altruism

2019 ◽  
Keyword(s):  
Animal Welfare ◽  
Poverty Alleviation ◽  
Future Generations ◽  
Global Poverty ◽  
Global Community ◽  
Helping Others ◽  
The World ◽  
Different Types ◽  
Effective Altruism

The effective altruism movement consists of a growing global community of people who organize significant parts of their lives around two key ideas, represented in its name. Altruism: If we use a significant portion of the resources in our possession—whether money, time, or talents—with a view to helping others, we can improve the world considerably. Effectiveness: When we do put such resources to altruistic use, it is crucial to focus on how much good this or that intervention is reasonably expected to do per unit of resource expended (for example, per dollar donated). While global poverty is a widely used case study in introducing and motivating effective altruism, if the ultimate aim is to do the most good one can with the resources expended, it is far from obvious that global poverty alleviation is highest priority cause area. In addition to ranking possible poverty-alleviation interventions against one another, we can also try to rank interventions aimed at very different types of outcome against one another. This includes, for example, interventions focusing on animal welfare or future generations. The scale and organization of the effective altruism movement encourage careful dialogue on questions that have perhaps long been there, throwing them into new and sharper relief, and giving rise to previously unnoticed questions. In the present volume, the first of its kind, a group of internationally recognized philosophers, economists, and political theorists contribute in-depth explorations of issues that arise once one takes seriously the twin ideas of altruistic commitment and effectiveness.

Transdiagnostic Approaches With Children

2018 ◽  
Author(s):  
Andrea B. Temkin ◽  
Mina Yadegar ◽  
Christine Cho ◽  
Brian C. Chu
Keyword(s):  
Mental Disorders ◽  
Externalizing Symptoms ◽  
Case Conceptualization ◽  
Common Elements ◽  
Transdiagnostic Treatment ◽  
Treatment Models ◽  
Different Types ◽  
Internalizing And Externalizing ◽  
Internalizing And Externalizing Symptoms

In recent years, the field of clinical psychology has seen a growing movement toward the research and development of transdiagnostic treatments. Transdiagnostic approaches have the potential to address numerous issues related to the development and treatment of mental disorders. Among these are the high rates of comorbidity across disorders, the increasing need for efficient protocols, and the call for treatments that can be more easily disseminated. This chapter provides a review of the current transdiagnostic treatment approaches for the treatment of youth mental disorders. Three different types of transdiagnostic protocols are examined: mechanism-based protocols, common elements treatments, and general treatment models that originated from single-disorder approaches to have broader reach. A case study illuminates how a mechanism-based approach would inform case conceptualization for a client presenting with internalizing and externalizing symptoms and how a transdiagnostic framework translates into practice.

scholarly journals Portable near Infrared Spectroscopy as a Tool for Fresh Tomato Quality Control Analysis in the Field

2021 ◽  
Vol 11 (7) ◽  
pp. 3209
Author(s):  
Karla R. Borba ◽  
Didem P. Aykas ◽  
Maria I. Milani ◽  
Luiz A. Colnago ◽  
Marcos D. Ferreira ◽  
...  
Keyword(s):  
Citric Acid ◽  
Near Infrared ◽  
Prediction Models ◽  
Quality Attributes ◽  
Internal Quality ◽  
Control Analysis ◽  
Tomato Quality ◽  
Wide Range ◽  
Different Types ◽  
Fresh Tomato

Portable spectrometers are promising tools that can be an alternative way, for various purposes, of analyzing food quality, such as monitoring in a few seconds the internal quality during fruit ripening in the field. A portable/handheld (palm-sized) near-infrared (NIR) spectrometer (Neospectra, Si-ware) with spectral range of 1295–2611 nm, equipped with a micro-electro-mechanical system (MEMs), was used to develop prediction models to evaluate tomato quality attributes non-destructively. Soluble solid content (SSC), fructose, glucose, titratable acidity (TA), ascorbic, and citric acid contents of different types of fresh tomatoes were analyzed with standard methods, and those values were correlated to spectral data by partial least squares regression (PLSR). Fresh tomato samples were obtained in 2018 and 2019 crops in commercial production, and four fruit types were evaluated: Roma, round, grape, and cherry tomatoes. The large variation in tomato types and having the fruits from distinct years resulted in a wide range in quality parameters enabling robust PLSR models. Results showed accurate prediction and good correlation (Rpred) for SSC = 0.87, glucose = 0.83, fructose = 0.87, ascorbic acid = 0.81, and citric acid = 0.86. Our results support the assertion that a handheld NIR spectrometer has a high potential to simultaneously determine several quality attributes of different types of tomatoes in a practical and fast way.

scholarly journals Model-Based Probabilistic Inversion Using Magnetic Data: A Case Study on the Kevitsa Deposit

Geosciences ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 150
Author(s):  
Nilgün Güdük ◽  
Miguel de la Varga ◽  
Janne Kaukolinna ◽  
Florian Wellmann
Keyword(s):  
Structural Parameters ◽  
Rock Properties ◽  
Magnetic Data ◽  
Geological Model ◽  
Borehole Data ◽  
Likelihood Functions ◽  
Different Types ◽  
Geophysical Information ◽  
Different Sources

Structural geological models are widely used to represent relevant geological interfaces and property distributions in the subsurface. Considering the inherent uncertainty of these models, the non-uniqueness of geophysical inverse problems, and the growing availability of data, there is a need for methods that integrate different types of data consistently and consider the uncertainties quantitatively. Probabilistic inference provides a suitable tool for this purpose. Using a Bayesian framework, geological modeling can be considered as an integral part of the inversion and thereby naturally constrain geophysical inversion procedures. This integration prevents geologically unrealistic results and provides the opportunity to include geological and geophysical information in the inversion. This information can be from different sources and is added to the framework through likelihood functions. We applied this methodology to the structurally complex Kevitsa deposit in Finland. We started with an interpretation-based 3D geological model and defined the uncertainties in our geological model through probability density functions. Airborne magnetic data and geological interpretations of borehole data were used to define geophysical and geological likelihoods, respectively. The geophysical data were linked to the uncertain structural parameters through the rock properties. The result of the inverse problem was an ensemble of realized models. These structural models and their uncertainties are visualized using information entropy, which allows for quantitative analysis. Our results show that with our methodology, we can use well-defined likelihood functions to add meaningful information to our initial model without requiring a computationally-heavy full grid inversion, discrepancies between model and data are spotted more easily, and the complementary strength of different types of data can be integrated into one framework.

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