Relevant bibliographies by topics / Classification of insurance products

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Academic literature on the topic 'Classification of insurance products'

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Published: 28 May 2022
Last updated: 29 May 2022

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Journal articles on the topic "Classification of insurance products"

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ЦОЙ, Марина, Marina . TSOI, Владислав ЩЕКОЛДИН, and Vladislav SHCHEKOLDIN. "STUDYING THE INSURANCE COMPANY CUSTOMERS PREFERENCES ON THE BASIS OF THE CONSENT CRITERIA USING CHAID-ANALYSIS." Services in Russia and abroad 11, no. 4 (July 4, 2017): 124–37. http://dx.doi.org/10.22412/1995-042x-11-4-10.

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The article considers modern trends in the insurance market development in the Russian Federation, and reviews the main insurance products and the dynamics of their implementation over the past few years. The authors identify the necessity for improving the insurance services quality, active work with consumers, and development of targeted packages of services, corresponding to the specific needs of individual customer segments. Based on the case of regional insurance company operating on the local insurance market in the city of Novosibirsk, the article analyzes the socio-demographic and economic characteristics and their impact on the probability of choosing insurance products. Using Pearson's chi-squared test, the authors have accomplished statistical review of 30 hypotheses in order to reveal the relationship between the characteristics of consumers and their choice of various insurance products. Using CHAID-analysis, the one of the most popular technologies for data mining, allowed authors to distinguish different homogeneous groups of consumers for each of the insurance products considered. Based on the study, the authors have constructed classification schemes of insurance services consumers. This led to the conclusion that age and marital status are most significant consumer characteristics for the segmentation. On the other hand, the study of the constructed consumer classification schemes shows that such indicators as “children" and "income" practically do not influence the choice of insurance products. Also, a study using CHAID-analysis made it possible to determine which types of insurance services allow the most effective joint combinations. In turn, it allowed to form four specially selected packages consisting of several insurance products to maximize the satisfaction of the company's customers.
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Wu, Bingyan, Xiaoqing An, Wei Sun, Xue Chang, and Huadong Su. "Construction of a Recommendation Method for Financial Insurance Products Based on Machine Learning." Mathematical Problems in Engineering 2022 (April 30, 2022): 1–7. http://dx.doi.org/10.1155/2022/6234947.

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In the era of the rise of big data, if insurance companies can effectively and reasonably use existing data to tap more potential information, it can not only improve work efficiency but also achieve precise marketing to customers, thereby saving costs. At the same time, China pays more and more attention to financial insurance, so it is of great significance to use customer information to explore the purchase behavior of financial insurance. This paper mainly analyzes the factors that affect the purchase of financial insurance from the aspects of individuals and families and provides references for insurance marketing. This paper selects the results of the China Comprehensive Social Survey in 2020 as the empirical sample data of this paper and sets whether to purchase financial insurance as the target variable. The characteristic variables were screened, and the 10 variables selected after screening were finally used to build the model. Next, the data are divided into training set and test set, and a decision tree learning model is established on the two data sets at the same time. The classification results of the model are evaluated according to the classification evaluation indicators. Finally, the decision tree analysis results provide suggestions and strategies for the construction of insurance marketing recommendation methods.
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Balaji, S., and S. K. Srivatsa. "Naïve Bayes Classification Approach for Mining Life Insurance Databases for Effective Prediction of Customer Preferences over Life Insurance Products." International Journal of Computer Applications 51, no. 3 (August 30, 2012): 22–26. http://dx.doi.org/10.5120/8023-0805.

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Zhao, Xuemei, Ting Lu, and Yonghui Dai. "Individual Driver Crash Risk Classification Based on IoV Data and Offline Consumer Behavior Data." Mobile Information Systems 2021 (June 12, 2021): 1–10. http://dx.doi.org/10.1155/2021/6784026.

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With the development of big data technologies, usage-based insurance (UBI) has received considerable attention from insurance companies. UBI products focus on identifying the relationship between the individual driver’s risk and online channel behavior variables from Internet of Vehicles (IoV) data. Although omnichannel information integration has promoted the development of many industries, it has not been used to improve the accuracy of driver risk classification models in insurance industries. This paper investigates the role of combining different channel variables in improving the classification of driver’s risk. Specifically, several models, including logistic regression and three different data mining techniques (neural networks, random forests, and support vector machines), augmented with driving behavior data based on the IoV and offline consumer behavior data collected from 4S (Sale, Spare part, Service, Survey) dealers, are applied to the classification model of risk. The empirical results show that the inclusion of online and offline channel data improves the different risk assessments; results also demonstrate the importance of offline consumer behavior variables in different models. These insights have important implications for insurance companies on UBI pricing strategy and cost management.
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Sasidharan, Soumya, V. K. Ranjith, and Sunitha Prabhuram. "Insurer’s Role in Intensifying Environmental Sustainability And Social Development." GATR Journal of Finance and Banking Review VOL. 6 (3) SEPTEMBER- DECEMBER 2021 6, no. 3 (December 30, 2021): 126–33. http://dx.doi.org/10.35609/jfbr.2021.6.3(2).

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Objective – Sustainable insurance is the new concept that emerges in the current state, that every country adopting now. The objective of the study is to identify the insurance industry's role and contribution to promoting environmental sustainability. To outline sustainable insurance and sustainable/green products and services. Methodology – This paper explores the contribution of the insurance industry and its role in promoting environmental sustainability and social development. This is a theoretical paper, focused on the secondary sources of data from research publications, websites, books, journals, and articles. To achieve the objectives, this study will critically review previous literature and assess contemporary views from different perspectives. Findings– Various insurers are frequently focusing on their progress, enhancing their share of the market, and maintaining better risks to achieve marketplace success. Insurers should always be on the lookout for new ways to set themselves apart from the competition. The implication for insurers is that their actions matter a lot when it comes to environmental issues and providing green insurance solutions can open new business opportunities for the industry. The answer may lie in marketing new products related to potential climate change and the corresponding sustainability/green insurance. Novelty – Sustainable insurance is aimed primarily at developing innovative or green products and services, reducing risk, improving company efficiency, and supporting environmental, social, and financial sustainability. There hasn't been a general overview of the role of insurers in enhancing environmental sustainability and social development done yet. Theoretically, our work aids policymakers and other stakeholders in better understanding the role of insurers in enhancing environmental sustainability and social development. Type of Paper: Review JEL Classification: G20, G22, G23. Keywords: Insurance, Sustainability, Green insurance, Green products and services, Sustainable Development.
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Bala, Ms Neetu, and Dr H. S. Sandhu. "Analysis of Factors Influencing Agents’ Perception towards Life Insurance Corporation of India." International Journal of Industrial Marketing 1, no. 1 (June 28, 2011): 88. http://dx.doi.org/10.5296/ijim.v1i1.897.

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Life Insurance Corporation of India, the capital intensive business, provides the most important financial instrument to customers aimed at protection as well as long term savings. The Corporation reaches out to the people through the main traditional route of the agency model for the selling processes of the numerous complex need-based products. The agents help in marketing its policies by spreading the message of life insurance among the masses. They serve as the kingpin for insurance companies seeking to provide traditional and innovative products, and focal point for customers seeking to procure insurance coverage and long term savings. The present paper investigates the factors influencing agents’ perception towards Life Insurance Corporation of India. The study is based on a sample of 225 respondents taken from three cities of Punjab. Factor Analytic Approach has been performed for data analysis. The results of the factor analysis reveal that Staff co-ordination is the most important factor to influence agents’ perception followed by other six factors namely: (i) Customer target; (ii) Competitive advantage predicates; (iii) Material hallmarks; (iv) Promising products and process; (v) Service enhancement; and (vi) Exclusive attention. Moreover, analysis of one way classification has also been performed to test the significant differences among the various groups of respondents across the 23-item perception scale. The results demonstrate that no significant differences exist among various groups of respondents with respect to their perception towards Life Insurance Corporation of India.
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Sun, Shuai, Jun Bi, Montserrat Guillen, and Ana M. Pérez-Marín. "Assessing Driving Risk Using Internet of Vehicles Data: An Analysis Based on Generalized Linear Models." Sensors 20, no. 9 (May 9, 2020): 2712. http://dx.doi.org/10.3390/s20092712.

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With the major advances made in internet of vehicles (IoV) technology in recent years, usage-based insurance (UBI) products have emerged to meet market needs. Such products, however, critically depend on driving risk identification and driver classification. Here, ordinary least square and binary logistic regressions are used to calculate a driving risk score on short-term IoV data without accidents and claims. Specifically, the regression results reveal a positive relationship between driving speed, braking times, revolutions per minute and the position of the accelerator pedal. Different classes of risk drivers can thus be identified. This study stresses both the importance and feasibility of using sensor data for driving risk analysis and discusses the implications for traffic safety and motor insurance.
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Cesarini, Luigi, Rui Figueiredo, Beatrice Monteleone, and Mario L. V. Martina. "The potential of machine learning for weather index insurance." Natural Hazards and Earth System Sciences 21, no. 8 (August 11, 2021): 2379–405. http://dx.doi.org/10.5194/nhess-21-2379-2021.

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Abstract. Weather index insurance is an innovative tool in risk transfer for disasters induced by natural hazards. This paper proposes a methodology that uses machine learning algorithms for the identification of extreme flood and drought events aimed at reducing the basis risk connected to this kind of insurance mechanism. The model types selected for this study were the neural network and the support vector machine, vastly adopted for classification problems, which were built exploring thousands of possible configurations based on the combination of different model parameters. The models were developed and tested in the Dominican Republic context, based on data from multiple sources covering a time period between 2000 and 2019. Using rainfall and soil moisture data, the machine learning algorithms provided a strong improvement when compared to logistic regression models, used as a baseline for both hazards. Furthermore, increasing the amount of information provided during the training of the models proved to be beneficial to the performances, increasing their classification accuracy and confirming the ability of these algorithms to exploit big data and their potential for application within index insurance products.
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Puzanova, Zh V., and M. A. Trifonova. "The role of insurance in the social-economic system." RUDN Journal of Sociology 20, no. 4 (December 15, 2020): 877–88. http://dx.doi.org/10.22363/2313-2272-2020-20-4-877-888.

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The article considers the position and meaning of insurance in the social-economic system of Russia. Insurance is associated primarily with protection of the property interests under risky events. There is a large classification of risks, which is closely related to the insurance institution, and the authors analyze some types of risks providing relevant contemporary examples. Insurance is a means of the risk management system; however, the current economic, political, and social situation has a direct impact on the insurance system. Thus, in periods of instability, insurance companies have to adapt to the economic situation and financial possibilities of people to purchase insurance products. Insurance as a type of activity performs two groups of functions - economic and social. The main task of insurance is to implement effective measures of insurance protection from risky events. The article also considers activities of insurers in Russia from 2012 to 2018: the number of insurance companies, the authorized capital, the peak volume of foreign deposits, insurance payments, reinsurance operations, etc. The authors present two types of insurance - voluntary and compulsory - and consider the features of each type. The data of sociological surveys allows to analyze these features and to identify the role of voluntary and compulsory insurance in the social-economic system (tasks, functions, and so on).
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Schmaltz, Christian, and Periklis Thivaios. "Are Credit Default Swaps Credit Default Insurances?" Journal of Applied Business Research (JABR) 30, no. 6 (October 29, 2014): 1819. http://dx.doi.org/10.19030/jabr.v30i6.8900.

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No, they are not. Although they exhibit similar cash flow patterns (economic perspective) this article argues that from a legal, accounting and regulatory perspective credit default swaps (CDS) are not considered to be an insurance contract. The protection buyer of a CDS is eligible to obtain the compensation without suffering any loss (and potentially realizing a gain) whereas insurance policies only pay out to compensate a loss (and not potentially realizing a gain). This disconnect between protection and exposure is the source for potential over-coverage. Furthermore, the concentrated set of reference entities and (interbank) counterparties as well as their tradeability make CDSs highly systemically significant products. Our conclusion is that CDSs are not default insurance policies. We propose to use default protection instead of credit default insurance to avoid the mislabelling. Furthermore, CDS have a substantial systemic risk potential which sharply contrasts to the limited systemic risk in the insurance industry. The legal classification of CDS as insurance contracts would have an enormous impact on the liquidity of CDS, as the ability of counterparties to issue and participate in CDS contracts would be limited.
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Dissertations / Theses on the topic "Classification of insurance products"

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Рябоконь, Н. П. "Виділення класифікаційних ознак страхових продуктів." Thesis, Українська академія банківської справи Національного банку України, 2011. http://essuir.sumdu.edu.ua/handle/123456789/62234.

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Rehder, Eike, and Jürgen Karla. "Adaption des Technology Acceptance Model für den Onlinevertrieb von Versicherungsprodukten." Technische Universität Dresden, 2010. https://tud.qucosa.de/id/qucosa%3A28016.

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Hao, Mingjie. "Insurance loss coverage under restricted risk classification." Thesis, University of Kent, 2017. https://kar.kent.ac.uk/62465/.

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Insurers hope to make profit through pooling policies from a large number of individuals. Unless the risk in question is similar for all potential customers, an insurer is exposed to the possibility of adverse selection by attracting only high-risk individuals. To counter this, insurers have traditionally employed underwriting principles, identifying suitable risk factors to subdivide their potential customers into homogeneous risk groups, based on which risk-related premiums can be charged. In reality, however, insurers may not have all the information reflecting individuals' risks due to information asymmetry or restrictions on using certain risk factors by regulators. In either case, conventional wisdom suggests that the absence of risk classification in an insurance market is likely to lead to a vicious circle: increasing premium with the prime aim to recover losses from over-subscription by high risks would lead to more low risks dropping out of the market; and eventually leading to a collapse of the whole insurance system, i.e. an adverse selection spiral. However, this concept is difficult to reconcile with the successful operation of many insurance markets, even in the presence of some restrictions on risk classification by regulators. Theoretical analysis of polices under asymmetric information began in the 1960s and 1970s (Arrow (1963), Pauly (1974), Rothschild & Stiglitz (1976)), by which time the adverse consequences of information asymmetry had already been widely accepted. However, empirical test results of its presence are mixed and varied by markets. Arguably from society's viewpoint, the high risks are those who most need insurance. That is, if the social purpose of insurance is to compensate the population's losses, then insuring high risks contributes more to this purpose than insuring low risks. In this case, restriction on risk classification may be reasonable, otherwise premium for high risks would be too high to be affordable. Thus, the traditional insurers' risk classification practices might be considered as contrary to this social purpose. To highlight this issue, ''loss coverage'' was introduced in Thomas (2008) as the expected population losses compensated by insurance. A higher loss coverage indicates that a higher proportion of the population's expected losses can be compensated by insurance. This might be a good result for the population as a whole. A corollary of this concept is that, from a public policy perspective, adverse selection might not always be a bad thing. The author argued that a moderate degree of adverse selection could be negated by the positive influence of loss coverage. Therefore, when analysing the impact of restricting insurance risk classification, loss coverage might be a better measure than adverse selection. In this thesis, we model the outcome in an insurance market where a pooled premium is charged as a result of an absence of risk-classification. The outcome is characterised by four quantities: equilibrium premium, adverse selection, loss coverage and social welfare. Social welfare is defined as the total expected utility of individuals (including those who buy insurance and those who do not buy insurance) at a given premium. Using a general family of demand functions (of which iso-elastic demand and negative-exponential demand are examples) with a non-decreasing demand elasticity function with respect to premium, we first analyse the case when low and high risk-groups have the same constant demand elasticity. Then we generalise the results to the case where demand elasticities could be different. In general, equilibrium premium and adverse selection increase monotonically with demand elasticity, but loss coverage first increases and then decreases. The results are consistent with the ideas proposed by Thomas (2008, 2009) that loss coverage will be increased if a moderate degree of adverse selection is tolerated. Furthermore, we are able to show that, for iso-elastic demand with equal demand elasticities for high and low risks, social welfare moves in the same direction as loss coverage, i.e. social welfare at pooled premium is higher than at risk-differentiated premiums, when demand elasticity is less than 1. Therefore, we argue that loss coverage may be a better measure than adverse selection to quantify the impact of risk classification scheme being restricted. Moreover, (observable) loss coverage could also be a useful proxy for social welfare, which depends on unobservable utility functions. Therefore, adverse election is not always a bad thing, if demand elasticity is sufficiently low. The research findings should add to the wider public policy debate on these issues and provide necessary research insights for informed decision making by actuaries, regulators, policyholders, insurers, policy-makers, capital providers and other stakeholders.
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Osman, Abdelghafour Mohamed. "Structured products: Pricing, hedging and applications for life insurance companies." Thesis, Uppsala University, Department of Mathematics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-119969.

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Khabele, Poloko. "Extending insurance products to the low-income market : broad guidelines." Thesis, Stellenbosch : Stellenbosch University, 2006. http://hdl.handle.net/10019.1/50606.

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Thesis (MBA)--Stellenbosch University, 2006.
ENGLISH ABSTRACT: This paper proposes broad guidelines that the formal insurance companies in South Africa should follow when entering the low-income market, specifically LSM 1-5. The guidelines follow on a SWOT analysis of the formal insurance providers present in the informal market. After discussing the risks that the poor face and the riskmitigating strategies that they employ, we identify the opportunities and threats of this market segment. The strengths and weaknesses of the formal institutions are deduced from observations of how the informal institutions supply the credit, savings on which the poor rely. Important lessons and principles that are conducive to servicing the needs of the poor are discussed. To break into this market requires new distribution channels, new products and premium collection methods. The guidelines therefore suggest that strategic alliances be established with informal institutions to enable leverage of their networks and knowledge and to streamline the process. New products designed should incorporate the social features of the informal institutions concerned. New technology, such as prepaid vouchers and vending machines, should be investigated as possible ways of collecting premiums through bank accounts.
AFRIKAANSE OPSOMMING: Hierdie dokument stel voor 'n wye gids wat die formele sektor van versekeraars in Suid-Afrika moet volg binne die lae-inkomste mark, spesifiek LSM 1-5. Hierdie riglyne is baseer op 'n SWOT-analise van formele versekerings verskaffers binne die informele mark. Eers moet die risiko en strategie wat die lae-inkomste sektor volg bespreek word, daarna moet die geleenthede en bedreigings van hierdie deel van die mark ge'identifiseer word. Die sterk- en swakhede van die formele en informele instellings moet waargeneem word, spesifiek hoe hulle krediet en versekerings produkte verskaf. 'n Baie belangrike aspek hiervan is hoe dienstig dit is vir die lae inkomste groepe. Om binne hierdie mark te breek, benodig dit nuwe verspreidings kanale, nuwe produkte en premium kollektiewe metodes. Hierdie riglyne benodig 'n strategiese bondgenootskap met informele instansies sodat dit die kennis en netwerke kan versterk in 'n vaartbelynde proses. Nuwe produkte wat ontwerp word moet sosiale aspekte van die informele sektor in ag neem. Nuwe tegnologie soos vooruitbetaalde kwitansie en muntautomaat masjiene moet ondersoek word as moontlike maniere om premies te kollekteer deur bank rekenings.
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Chu, Chi Chiu. "Pricing models of equity-linked insurance products and LIBOR exotic derivatives /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?MATH%202005%20CHU.

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MORGADO, WILSON LINS. "APPLYING RISK CLASSIFICATION METHOD IN CAR INSURANCE MARKET." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2004. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=5932@1.

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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
A estimação do risco em seguros de automóveis representa um difícil problema de regressão. As dificuldades vão desde a utilização de um grande número de variáveis discretas como explicativas, até a distribuição particular dos ruídos e uma quantidade expressiva de categorias com valores nulos e valores discrepantes. Supondo que os problemas de estimação estejam relacionados com a classificação do risco adotada pelo mercado, este trabalho propõe um método de classificação alternativo. O método desenvolvido foi baseado na técnica de análise fatorial, e no algoritmo de agrupamento de dados denominado fuzzy clustering system. Para avaliar a eficiência do método em solucionar os problemas de estimação, optou-se por utilizar o erro resultante da aplicação de modelos lineares generalizados. Ao final, o erro de estimação obtido diante da classificação proposta, foi comparado ao obtido diante da classificação usual de mercado.
The estimation of car insurance risk rate represents a difficult regression problem. One of the difficulties of this problem is the use of a number of discrete independent variables and a specific error distribution that presents an expressive number of null and outlier values. Assuming that these estimation problems are related to the risk classification adopted by the insurance companies, this work proposes an alternative classification method. This method is based on factorial analysis techniques and on the algorithm known as Fuzzy Clustering System. To evaluate the efficiency of this method in solving the problems identified, the risk was estimated using generalized linear models. The errors from each model were obtained and compared between classifications.
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Philipps, Jörg [Verfasser]. "Pricing and Hedging of Unit-Linked Life Insurance Products / Jörg Philipps." München : Verlag Dr. Hut, 2012. http://d-nb.info/1025821246/34.

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Postigo, Smura Michel Alexander. "Cluster analysis on sparse customer data on purchase of insurance products." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-249558.

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This thesis work aims at performing a cluster analysis on customer data of insurance products. Three different clustering algorithms are investigated. These are K-means (center-based clustering), Two-Level clustering (SOM and Hierarchical clustering) and HDBSCAN (density-based clustering). The input to the algorithms is a high-dimensional and sparse data set. It contains information about the customers previous purchases, how many of a product they have bought and how much they have paid. The data set is partitioned in four different subsets done with domain knowledge and also preprocessed by normalizing respectively scaling before running the three different cluster algorithms on it. A parameter search is performed for each of the cluster algorithms and the best clustering is compared with the other results. The best is measured by the highest average silhouette index. The results indicates that all of the three algorithms performs approximately equally good, with single exceptions. However, it can be stated that the algorithm showing best general results is K-means on scaled data sets. The different preprocessings and partitions of the data impacts the results in different ways and this shows that it is important to preprocess the input data in several ways when performing a cluster analysis.
Målet med detta examensarbete är att utföra en klusteranalys på kunddata av försäkringsprodukter. Tre olika klusteralgoritmer undersöks. Dessa är Kmeans (center-based clustering), Two-Level clustering (SOM och Hierarchical clustering) och HDBSCAN (density-based clustering). Input till algoritmerna är ett högdimensionellt och glest dataset. Det innhåller information om kundernas tidigare köp, hur många produkter de har köpt och hur mycket de har betalat. Datasetet delas upp i fyra delmängder med kunskap inom området och förarbetas också genom att normaliseras respektive skalas innan klustringsalgoritmerna körs på det. En parametersökning utförs för dem tre olika algoritmerna och den bästa klustringen jämförs med de andra resultaten. Den bästa algoritmen bestäms genom att beräkna the högsta silhouette index-medelvärdet. Resultaten indikerar att alla tre algoritmerna levererar ungefärligt lika bra resultat, med enstaka undantag. Dock, kan det bekräftas att algoritmen som visar bäst resultat överlag är K-means på skalade dataset. De olika förberedelserna och uppdelningarna av datasetet påverkar resultaten på olika sätt och detta tyder på vikten av att förbereda input datat på flera sätt när en klusteranalys utförs.
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Trottier, Denis-Alexandre. "Essays on modeling, hedging and pricing of insurance and financial products." Doctoral thesis, Université Laval, 2018. http://hdl.handle.net/20.500.11794/29926.

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Cette thèse est composée de trois articles abordant différentes problématiques en relation avec la modélisation, la couverture et la tarification des risques d’assurance et financiers. “A general class of distortion operators for pricing contingent claims with applications to CAT bonds” est un projet présentant une méthode générale pour dériver des opérateurs de distorsion compatibles avec la valorisation sans arbitrage. Ce travail offre également une nouvelle classe simple d’opérateurs de distorsion afin d’expliquer les primes observées dans le marché des obligations catastrophes. “Local hedging of variable annuities in the presence of basis risk” est un travail dans lequel une méthode de couverture des rentes variables en présence de risque de base est développée. La méthode de couverture proposée bénéficie d’une exposition plus élevée au risque de marché et d’une diversification temporelle du risque pour obtenir un rendement excédentaire et faciliter l’accumulation de capital. “Option pricing under regime-switching models : Novel approaches removing path-dependence” est un projet dans lequel diverses mesures neutres au risque sont construites pour les modèles à changement de régime de manière à générer des processus de prix d’option qui ne présentent pas de dépendance au chemin, en plus de satisfaire d’autres propriétés jugées intuitives et souhaitables.
This thesis is composed of three papers addressing different issues in relation to the modeling, hedging and pricing of insurance and financial risks. “A general class of distortion operators for pricing contingent claims with applications to CAT bonds” is a project presenting a general method for deriving probability distortion operators consistent with arbitrage-free pricing. This work also offers a simple novel class of distortions operators for explaining catastrophe (CAT) bond spreads. “Local hedging of variable annuities in the presence of basis risk” is a work in which a method to hedge variable annuities in the presence of basis risk is developed. The proposed hedging scheme benefits from a higher exposure to equity risk and from time diversification of risk to earn excess return and facilitate the accumulation of capital. “Option pricing under regime-switching models: Novel approaches removing path-dependence” is a project in which various risk-neutral measures for hidden regime-switching models are constructed in such a way that they generate option price processes which do not exhibit path-dependence in addition to satisfy other properties deemed intuitive and desirable.
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Books on the topic "Classification of insurance products"

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Billah, Mohd Ma'Sum. Islamic Insurance Products. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17681-5.

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Flitner, Arthur L. Surplus lines insurance products. Malvern, PA: American Institute for Chartered Property Casualty Underwriters/Insurance Institute of America, 2006.

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Kreidler, Mike. Deregulation of commercial products. [Olympia, Wash.]: Washington State Office of the Insurance Commissioner, 2001.

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Okumura, Kirk S. Essentials of multiline insurance products. 2nd ed. Bryn Mawr, PA: American College Press, 2011.

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Okumura, Kirk S. Essentials of multiline insurance products. Bryn Mawr, PA: The American College Press, 2009.

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Stevick, Glenn E. Essentials of life insurance products. 3rd ed. Bryn Mawr, PA: American College Press, 2011.

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United States. Office of Management and Budget. Standard industrial classification manual. [Washington: OMB], 1987.

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Tantō), Japan Sōmushō Seisaku Tōkatsukan (Tōkei Kijun. Japan standard industrial classification. [Tokyo]: Director-General for Policy Planning(Statistical Standards), Ministry of Internal Affairs and Communications, 2007.

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Office, United Nations Statistical. Provisional central product classification. New York: United Nations, 1991.

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Association, Life Office Management, ed. Regulatory compliance: Insurance and annuity products. Atlanta, GA: LOMA, 1998.

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Book chapters on the topic "Classification of insurance products"

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Cipra, Tomas. "Insurance Classification." In Financial and Insurance Formulas, 143–48. Heidelberg: Physica-Verlag HD, 2010. http://dx.doi.org/10.1007/978-3-7908-2593-0_16.

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Pitacco, Ermanno. "Health Insurance Products." In Health Insurance, 29–62. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12235-9_3.

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Billah, Mohd Ma’Sum. "Re-takaful Products." In Islamic Insurance Products, 407–15. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17681-5_35.

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Denuit, Michel, Donatien Hainaut, and Julien Trufin. "Insurance Risk Classification." In Springer Actuarial, 3–26. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25820-7_1.

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Billah, Mohd Ma’Sum. "Preview of Islamic Life Insurance Products." In Islamic Insurance Products, 247–69. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17681-5_20.

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Billah, Mohd Ma’Sum. "An Overview of Takaful Products." In Islamic Insurance Products, 3–27. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17681-5_1.

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Billah, Mohd Ma’Sum. "Health Takaful Rider Plan." In Islamic Insurance Products, 147–57. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17681-5_10.

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Billah, Mohd Ma’Sum. "Group Takaful Plan." In Islamic Insurance Products, 159–66. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17681-5_11.

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Billah, Mohd Ma’Sum. "Group Takaful Plan for Health Care." In Islamic Insurance Products, 167–80. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17681-5_12.

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Billah, Mohd Ma’Sum. "Pilgrimage (Hajj) Takaful." In Islamic Insurance Products, 181–87. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17681-5_13.

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Conference papers on the topic "Classification of insurance products"

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Korn, Ralf, and Andreas Wagner. "Chance-Risk Classification of Pension Products: Scientific Concepts and Challenges." In Innovations in Insurance, Risk- and Asset Management. WORLD SCIENTIFIC, 2018. http://dx.doi.org/10.1142/9789813272569_0015.

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Bakar, Azuraliza Abu, Zalinda Othman, Mohd Saiful Nizam Md Yusoff, and Ruhaizan Ismail. "Development of knowledge model for insurance product decision using the associative classification approach." In 2010 10th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2010. http://dx.doi.org/10.1109/isda.2010.5687120.

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Ferezagia, Debrina. "Sales of Life Insurance Products in Indonesia: InsurTech and Traditional Insurance Agents." In The International Conference of Vocational Higher Education (ICVHE) “Empowering Human Capital Towards Sustainable 4.0 Industry”. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0010029700002967.

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Sohail, Misbah, Pedro Peres, and Yuhua Li. "Feature Importance Analysis for Customer Management of Insurance Products." In 2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021. http://dx.doi.org/10.1109/ijcnn52387.2021.9533893.

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Vij, Aabhas, and N. Preethi. "Approaches Towards A Recommendation Engine For Life Insurance Products." In 2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC). IEEE, 2021. http://dx.doi.org/10.1109/icmnwc52512.2021.9688436.

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Muller, Daniel, and Yiea-Funk Te. "Insurance premium optimization using motor insurance policies — A business growth classification approach." In 2017 IEEE International Conference on Big Data (Big Data). IEEE, 2017. http://dx.doi.org/10.1109/bigdata.2017.8258437.

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Guo, Yan, Yu Zhou, Xiaonan Hu, and Wenchuan Cheng. "Research on Recommendation of Insurance Products Based on Random Forest." In 2019 International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI). IEEE, 2019. http://dx.doi.org/10.1109/mlbdbi48998.2019.00069.

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Krugerova, Martina. "DIFFICULTIES OF GENERAL DATA PROTECTION REGULATION APPLICATION TO INSURANCE PRODUCTS DISTRIBUTION." In 5th International Multidisciplinary Scientific Conferences on SOCIAL SCIENCES and ARTS SGEM2018. STEF92 Technology, 2018. http://dx.doi.org/10.5593/sgemsocial2018/1.2/s02.068.

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Dongwei, Xu. "Irrationality in automobile insurance classification: Analysis of one problem in China automobile insurance market." In 2011 IEEE 3rd International Conference on Communication Software and Networks (ICCSN). IEEE, 2011. http://dx.doi.org/10.1109/iccsn.2011.6014224.

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Gunadi, Farhan, Muhammad Fauzi, Bagas Firdaus, and Afrida Helen. "Preprocessing Application for Car Insurance Claim Classification Model." In 2021 International Conference on Artificial Intelligence and Big Data Analytics (ICAIBDA). IEEE, 2021. http://dx.doi.org/10.1109/icaibda53487.2021.9689717.

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Reports on the topic "Classification of insurance products"

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Fetterer, F., and D. Gineris. Evaluating ERS-1 Ice Motion and Classification Products. Fort Belvoir, VA: Defense Technical Information Center, March 1993. http://dx.doi.org/10.21236/ada267614.

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Vernooij, Eric, Valerie Rautureau, Atanas Koulov, Mitsutaka Shiraski, Alex Artau, and Scott Ewan. standardized methodology to support particle investigations and classification in biopharmaceutical parenteral products. BioPhorum, November 2021. http://dx.doi.org/10.46220/2021ff006.

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Bland, Gary, Lucrecia Peinado, and Christin Stewart. Innovations for Improving Access to Quality Health Care: The Prospects for Municipal Health Insurance in Guatemala. RTI Press, December 2017. http://dx.doi.org/10.3768/rtipress.2017.pb.0016.1712.

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Municipal insurance–a collective compact in which municipal government is the lead actor in designing, delivering, and supervising a health care financing arrangement—is considered by some Guatemalans as a potential new avenue for improving financial protection against rising costs and improved access to quality health care. This brief presents a political economy analysis of the prospects for the adoption of municipal insurance in Guatemala. Municipal insurance has so far been tried only once, in 2015, by the large suburban municipality of Villa Nueva. Drawing from the Villa Nueva experience, based on interviews with nearly 30 key informants, this brief examines the potential obstacles to municipal insurance reform as well as leading factors favoring its introduction. Consistent health ministry support and equity concerns are potential limitations, for example, while decentralization and the recent emergence of creative insurance products are likely to be supportive. This brief then concludes with consideration of the policy implications of such a reform. We also offer a series of policy recommendations for policymakers and practitioners who may be looking to implement municipal insurance reform.
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Ramm-Granberg, Tynan, F. Rocchio, Catharine Copass, Rachel Brunner, and Eric Nelsen. Revised vegetation classification for Mount Rainier, North Cascades, and Olympic national parks: Project summary report. National Park Service, February 2021. http://dx.doi.org/10.36967/nrr-2284511.

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Field crews recently collected more than 10 years of classification and mapping data in support of the North Coast and Cascades Inventory and Monitoring Network (NCCN) vegetation maps of Mount Rainier (MORA), Olympic (OLYM), and North Cascades (NOCA) National Parks. Synthesis and analysis of these 6000+ plots by Washington Natural Heritage Program (WNHP) and Institute for Natural Resources (INR) staff built on the foundation provided by the earlier classification work of Crawford et al. (2009). These analyses provided support for most of the provisional plant associations in Crawford et al. (2009), while also revealing previously undescribed vegetation types that were not represented in the United States National Vegetation Classification (USNVC). Both provisional and undescribed types have since been submitted to the USNVC by WNHP staff through a peer-reviewed process. NCCN plots were combined with statewide forest and wetland plot data from the US Forest Service (USFS) and other sources to create a comprehensive data set for Washington. Analyses incorporated Cluster Analysis, Nonmetric Multidimensional Scaling (NMS), Multi-Response Permutation Procedure (MRPP), and Indicator Species Analysis (ISA) to identify, vet, and describe USNVC group, alliance, and association distinctions. The resulting revised classification contains 321 plant associations in 99 alliances. A total of 54 upland associations were moved through the peer review process and are now part of the USNVC. Of those, 45 were provisional or preliminary types from Crawford et al. (2009), with 9 additional new associations that were originally identified by INR. WNHP also revised the concepts of 34 associations, wrote descriptions for 2 existing associations, eliminated/archived 2 associations, and created 4 new upland alliances. Finally, WNHP created 27 new wetland alliances and revised or clarified an additional 21 as part of this project (not all of those occur in the parks). This report and accompanying vegetation descriptions, keys and synoptic and environmental tables (all products available from the NPS Data Store project reference: https://irma.nps.gov/DataStore/Reference/Profile/2279907) present the fruit of these combined efforts: a comprehensive, up-to-date vegetation classification for the three major national parks of Washington State.
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Lasko, Kristofer, and Sean Griffin. Monitoring Ecological Restoration with Imagery Tools (MERIT) : Python-based decision support tools integrated into ArcGIS for satellite and UAS image processing, analysis, and classification. Engineer Research and Development Center (U.S.), April 2021. http://dx.doi.org/10.21079/11681/40262.

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Monitoring the impacts of ecosystem restoration strategies requires both short-term and long-term land surface monitoring. The combined use of unmanned aerial systems (UAS) and satellite imagery enable effective landscape and natural resource management. However, processing, analyzing, and creating derivative imagery products can be time consuming, manually intensive, and cost prohibitive. In order to provide fast, accurate, and standardized UAS and satellite imagery processing, we have developed a suite of easy-to-use tools integrated into the graphical user interface (GUI) of ArcMap and ArcGIS Pro as well as open-source solutions using NodeOpenDroneMap. We built the Monitoring Ecological Restoration with Imagery Tools (MERIT) using Python and leveraging third-party libraries and open-source software capabilities typically unavailable within ArcGIS. MERIT will save US Army Corps of Engineers (USACE) districts significant time in data acquisition, processing, and analysis by allowing a user to move from image acquisition and preprocessing to a final output for decision-making with one application. Although we designed MERIT for use in wetlands research, many tools have regional or global relevancy for a variety of environmental monitoring initiatives.
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Evans, Julie, Kendra Sikes, and Jamie Ratchford. Vegetation classification at Lake Mead National Recreation Area, Mojave National Preserve, Castle Mountains National Monument, and Death Valley National Park: Final report (Revised with Cost Estimate). National Park Service, October 2020. http://dx.doi.org/10.36967/nrr-2279201.

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Vegetation inventory and mapping is a process to document the composition, distribution and abundance of vegetation types across the landscape. The National Park Service’s (NPS) Inventory and Monitoring (I&M) program has determined vegetation inventory and mapping to be an important resource for parks; it is one of 12 baseline inventories of natural resources to be completed for all 270 national parks within the NPS I&M program. The Mojave Desert Network Inventory & Monitoring (MOJN I&M) began its process of vegetation inventory in 2009 for four park units as follows: Lake Mead National Recreation Area (LAKE), Mojave National Preserve (MOJA), Castle Mountains National Monument (CAMO), and Death Valley National Park (DEVA). Mapping is a multi-step and multi-year process involving skills and interactions of several parties, including NPS, with a field ecology team, a classification team, and a mapping team. This process allows for compiling existing vegetation data, collecting new data to fill in gaps, and analyzing the data to develop a classification that then informs the mapping. The final products of this process include a vegetation classification, ecological descriptions and field keys of the vegetation types, and geospatial vegetation maps based on the classification. In this report, we present the narrative and results of the sampling and classification effort. In three other associated reports (Evens et al. 2020a, 2020b, 2020c) are the ecological descriptions and field keys. The resulting products of the vegetation mapping efforts are, or will be, presented in separate reports: mapping at LAKE was completed in 2016, mapping at MOJA and CAMO will be completed in 2020, and mapping at DEVA will occur in 2021. The California Native Plant Society (CNPS) and NatureServe, the classification team, have completed the vegetation classification for these four park units, with field keys and descriptions of the vegetation types developed at the alliance level per the U.S. National Vegetation Classification (USNVC). We have compiled approximately 9,000 existing and new vegetation data records into digital databases in Microsoft Access. The resulting classification and descriptions include approximately 105 alliances and landform types, and over 240 associations. CNPS also has assisted the mapping teams during map reconnaissance visits, follow-up on interpreting vegetation patterns, and general support for the geospatial vegetation maps being produced. A variety of alliances and associations occur in the four park units. Per park, the classification represents approximately 50 alliances at LAKE, 65 at MOJA and CAMO, and 85 at DEVA. Several riparian alliances or associations that are somewhat rare (ranked globally as G3) include shrublands of Pluchea sericea, meadow associations with Distichlis spicata and Juncus cooperi, and woodland associations of Salix laevigata and Prosopis pubescens along playas, streams, and springs. Other rare to somewhat rare types (G2 to G3) include shrubland stands with Eriogonum heermannii, Buddleja utahensis, Mortonia utahensis, and Salvia funerea on rocky calcareous slopes that occur sporadically in LAKE to MOJA and DEVA. Types that are globally rare (G1) include the associations of Swallenia alexandrae on sand dunes and Hecastocleis shockleyi on rocky calcareous slopes in DEVA. Two USNVC vegetation groups hold the highest number of alliances: 1) Warm Semi-Desert Shrub & Herb Dry Wash & Colluvial Slope Group (G541) has nine alliances, and 2) Mojave Mid-Elevation Mixed Desert Scrub Group (G296) has thirteen alliances. These two groups contribute significantly to the diversity of vegetation along alluvial washes and mid-elevation transition zones.
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Papasodoro, C., D. Bélanger, G. Légaré-Couture, P. Tardif, and M. Turgeon-Pelchat. Mise à jour de la Stratégie nationale sur les données d'élévation, automne 2021. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329336.

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The National Elevation Data Strategy is being implemented. This newsletter of October 2021 provides an update on the following: 1. Status of the 2021 LiDAR acquisitions 2. New elevation products and data 3. Improvement of the automatic extraction of building footprints 4. Validation of LiDAR classification by artificial intelligence.
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Papasodoro, C., D. Bélanger, G. Légaré-Couture, P. Tardif, and M. Turgeon-Pelchat. National Elevation Data Strategy update, fall 2021. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329335.

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The National Elevation Data Strategy is being implemented. This newsletter of October 2021 provides an update on the following: 1. Status of the 2021 LiDAR acquisitions 2. New elevation products and data 3. Improvement of the automatic extraction of building footprints 4. Validation of LiDAR classification by artificial intelligence.
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Gindi, Renee. Health, United States, 2019. Centers for Disease Control and Prevention (U.S.), 2021. http://dx.doi.org/10.15620/cdc:100685.

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Health, United States, 2019 is the 43rd report on the health status of the nation and is submitted by the Secretary of the Department of Health and Human Services to the President and the Congress of the United States in compliance with Section 308 of the Public Health Service Act. This report was compiled by the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). The Health, United States series presents an annual overview of national trends in key health indicators. The 2019 report presents trends and current information on selected measures of morbidity, mortality, health care utilization and access, health risk factors, prevention, health insurance, and personal health care expenditures in a 20-figure chartbook. The Health, United States, 2019 Chartbook is supplemented by several other products including Trend Tables, an At-a-Glance table, and Appendixes available for download on the Health, United States website at: https://www.cdc.gov/nchs/hus/ index.htm. The Health, United States, 2019 Chartbook contains 20 figures and 20 tables on health and health care in the United States. Examining trends in health informs the development, implementation, and evaluation of health policies and programs. The first section (Figures 1–13) focuses on health status and determinants: life expectancy, infant mortality, selected causes of death, overdose deaths, suicide, maternal mortality, teen births, preterm births, use of tobacco products, asthma, hypertension, heart disease and cancer, and functional limitations. The second section (Figures 14–15) presents trends in health care utilization: use of mammography and colorectal tests and unmet medical needs. The third section (Figures 16–17) focuses on health care resources: availability of physicians and dentists. The fourth section (Figures 18–20) describes trends in personal health care expenditures, health insurance coverage, and supplemental insurance coverage among Medicare beneficiaries. The Highlights section summarizes major findings from the Chartbook. Suggested citation: National Center for Health Statistics. Health, United States, 2019. Hyattsville, MD. 2021.
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Delwiche, Michael, Yael Edan, and Yoav Sarig. An Inspection System for Sorting Fruit with Machine Vision. United States Department of Agriculture, March 1996. http://dx.doi.org/10.32747/1996.7612831.bard.

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Concepts for real-time grading of fruits and vegetables were developed, including multi-spectral imaging with structured illumination to detect and distinguish surface defects from concavities. Based on these concepts, a single-lane conveyor and inspection system were designed and evaluated. Image processing algorithms were developed to inspect and grade large quasi-spherical fruits (peaches and apples) and smaller dried fruits (dates). Adjusting defect pixel thresholds to achieve a 25% error rate on good apples, classification errors for bruise, crack, and cut classes were 51%, 42%, and 46%, respectively. Comparable results for bruise, scar, and cut peach clases were 48%, 22%, and 58%, respectively. Acquiring more than two images of each fruit and using more than six lines of structured illumination per fruit would reduce sorting errors. Doing so, potential sorting error rates for bruise, crack, and cut apple classes were estimated to be 38%, 38%, and 33%, respectively. Similarly, potential error rates for the bruitse, scar, and cut peach classes were 9%, 3%, and 30%, respectively. Date size classification results were good: 68% within one size class and 98% within two size classes. Date quality classification results were not adequate due to the problem of blistering. Improved features were discussed. The most significant contribution of this research was the on-going collaboration with producers and equipment manufacturers, and the resulting transfer of research ideas to expedite the commercial application of machine vision for postharvest inspection and grading of agricultural products.
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