Relevant bibliographies by topics / Attribute estimation

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Attribute estimation'

Author: Grafiati
Published: 10 March 2023
Last updated: 11 March 2023

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Journal articles on the topic "Attribute estimation"

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Kawai, Hiroya, Koichi Ito, and Takafumi Aoki. "Face Attribute Estimation Using Multi-Task Convolutional Neural Network." Journal of Imaging 8, no. 4 (April 10, 2022): 105. http://dx.doi.org/10.3390/jimaging8040105.

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Face attribute estimation can be used for improving the accuracy of face recognition, customer analysis in marketing, image retrieval, video surveillance, and criminal investigation. The major methods for face attribute estimation are based on Convolutional Neural Networks (CNNs) that solve face attribute estimation as a multiple two-class classification problem. Although one feature extractor should be used for each attribute to explore the accuracy of attribute estimation, in most cases, one feature extractor is shared to estimate all face attributes for the parameter efficiency. This paper proposes a face attribute estimation method using Merged Multi-CNN (MM-CNN) to automatically optimize CNN structures for solving multiple binary classification problems to improve parameter efficiency and accuracy in face attribute estimation. We also propose a parameter reduction method called Convolutionalization for Parameter Reduction (CPR), which removes all fully connected layers from MM-CNNs. Through a set of experiments using the CelebA and LFW-a datasets, we demonstrate that MM-CNN with CPR exhibits higher efficiency of face attribute estimation in terms of estimation accuracy and the number of weight parameters than conventional methods.
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Duan, Shunran, Longlong Jiao, Meijuan Yin, and Lanlan Yü. "DADDE:deep anomaly detection with density estimation." Journal of Physics: Conference Series 2294, no. 1 (June 1, 2022): 012017. http://dx.doi.org/10.1088/1742-6596/2294/1/012017.

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Abstract The problem of abnormal nodes detection in attributed network is widely used in daily life, such as social networks, cyberspace security, financial fields and so on. Most existing detection methods ignore the relationship between structure information and attribute information in attributed network. Although some methods consider the relationship between them, but it can’t distinguish the types of abnormal nodes well, that is, attribute exceptions or structural exceptions. Aiming at the shortcomings of existing methods, this paper proposes a deep anomaly detection model combining density estimation. The idea of detecting abnormal nodes by reconstruction error is used, the structure information and attribute information of attributed network are reconstructed respectively, and abnormal nodes are detected by density estimation based on reconstruction error and embedding vector of nodes. In this paper, the validity of DADDE model is proved by experiments on three commonly used data sets in this field.
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Subroto, Agus. "SIKAP KONSUMEN TERHADAP ATRIBUT-ATRIBUT YANG DITAWARKAN TOKO BUKU GRAMEDIA DI SURABAYA." Manajemen & Bisnis Jurnal 4, no. 2 (September 5, 2018): 1–19. http://dx.doi.org/10.37303/embeji.v4i2.101.

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This research aim to identitication and to know consumer attitude towards attributes that offered by Gramedia book store in Surabaya, that attributes are : product, price, promotion, location, distribution and facility as independent variable and consumer attitude as dependent variable. To analysis that costumer attitude use Multiatribute Attitude Model (MAM) that substance of consumer satisfaction determined by weight which given consumer to attribute (i) times by difference consumer ideal to attribute (i) by consumer beliefing to attribute (i) accounting of measuring scale use likert scale by five estimation category which each estimation category qualificated by give weight. The results of the study prove that consumers have a positive attitude towards the attributes offered and the most influential attribute is location. Keywords: consumers attitude, attributes.
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Subroto, Agus. "SIKAP KONSUMEN TERHADAP ATRIBUT-ATRIBUT YANG DITAWARKAN TOKO BUKU GRAMEDIA DI SURABAYA." Manajemen & Bisnis Jurnal 4, no. 2 (September 5, 2019): 18–36. http://dx.doi.org/10.37303/embeji.v4i2.74.

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This research aim to identitication and to know consumer attitude towards attributes that offered by Gramedia book store in Surabaya, that attributes are : product, price, promotion, location, distribution and facility as independent variable and consumer attitude as dependent variable. To analysis that costumer attitude use Multiatribute Attitude Model (MAM) that substance of consumer satisfaction determined by weight which given consumer to attribute (i) times by difference consumer ideal to attribute (i) by consumer beliefing to attribute (i) accounting of measuring scale use likert scale by five estimation category which each estimation category qualificated by give weight. The results of the study prove that consumers have a positive attitude towards the attributes offered and the most influential attribute is location. Keywords: consumers attitude, attributes.
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Al-Ali, Mustafa, Richard Hastings-James, Mohammad Makkawi, and Gabor Korvin. "Vibrator attribute leading velocity estimation." Leading Edge 22, no. 5 (May 2003): 400–405. http://dx.doi.org/10.1190/1.1579571.

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Yu, Xiao Feng, Zhao Sheng Luo, Chun Lei Gao, and Yu Jun Li. "Influence of Attributes Relationship to Parameter Estimation in DINA." Advanced Materials Research 940 (June 2014): 491–94. http://dx.doi.org/10.4028/www.scientific.net/amr.940.491.

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DINA model appreciated by many researchers considers the relationships among attributes as mutually independent, conjunction and non-compensation relationship, but in real applications, there may not be able to meet such a relationship. Study the impacts on parameter estimates for the DINA model because of attribute relationships. Simulation results show that when there is a hierarchical relationship between attributes, there will be a great impact on the parameter estimation accuracy of DINA model; and the parameter estimation accuracy mainly affected by attribute hierarchy and the number of subjects. When existing hierarchy relationships among attributes, using DINA model as cognitive diagnosis model would affect the validity of diagnostic tests.
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LI, JINGZHOU, and GUENTHER RUHE. "SOFTWARE EFFORT ESTIMATION BY ANALOGY USING ATTRIBUTE SELECTION BASED ON ROUGH SET ANALYSIS." International Journal of Software Engineering and Knowledge Engineering 18, no. 01 (February 2008): 1–23. http://dx.doi.org/10.1142/s0218194008003532.

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Estimation by analogy (EBA) predicts effort for a new project by learning from the performance of former projects. This is done by aggregating effort information of similar projects from a given historical data set that contains projects, or objects in general, and attributes describing the objects. While this has been successful in general, existing research results have shown that a carefully selected subset, as well as weighting, of the attributes may improve the performance of the estimation methods. In order to improve the estimation accuracy of our former proposed EBA method AQUA, which supports data sets that have non-quantitative and missing values, an attribute weighting method using rough set analysis is proposed in this paper. AQUA is thus extended to AQUA+ by incorporating the proposed attribute weighting and selection method. Better prediction accuracy was obtained by AQUA+ compared to AQUA for five data sets. The proposed method for attribute weighting and selection is effective in that (1) it supports data sets that have non-quantitative and missing values; (2) it supports attribute selection as well as weighting, which are not supported simultaneously by other attribute selection methods; and (3) it helps AQUA+ to produce better performance.
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Tu, Dongbo, Shiyu Wang, Yan Cai, Jeff Douglas, and Hua-Hua Chang. "Cognitive Diagnostic Models With Attribute Hierarchies: Model Estimation With a Restricted Q-Matrix Design." Applied Psychological Measurement 43, no. 4 (April 16, 2018): 255–71. http://dx.doi.org/10.1177/0146621618765721.

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Attribute hierarchy is a common assumption in the educational context, where the mastery of one attribute is assumed to be a prerequisite to the mastery of another one. The attribute hierarchy can be incorporated through a restricted Q matrix that implies the specified structure. The latent class–based cognitive diagnostic models (CDMs) usually do not assume a hierarchical structure among attributes, which means all profiles of attributes are possible in a population of interest. This study investigates different estimation methods to the classification accuracy for a family of CDMs when they are combined with a restricted Q-matrix design. A simulation study is used to explain the misclassification caused by an unrestricted estimation procedure. The advantages of the restricted estimation procedure utilizing attribute hierarchies for increased classification accuracy are also further illustrated through a real data analysis on a syllogistic reasoning diagnostic assessment. This research can provide guidelines for educational and psychological researchers and practitioners when they use CDMs to analyze the data with a restricted Q-matrix design and make them be aware of the potentially contaminated classification results if ignoring attribute hierarchies.
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Chen, Yingbing, John A. Kershaw, Yung-Han Hsu, and Ting-Ru Yang. "Carbon estimation using sampling to correct LiDAR-assisted enhanced forest inventory estimates." Forestry Chronicle 96, no. 01 (May 2020): 9–19. http://dx.doi.org/10.5558/tfc2020-003.

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Light Detection and Ranging (LiDAR) scanning has been increasingly applied in forest ecosystem surveys. Data from LiDAR describe forest structure and provide attribute information for forest inventory. These attributes can potentially aid in the estimation of biomass and carbon by providing sampling covariates. Therefore, this study explored the accuracy of estimating carbon storage by calibrating LiDAR attributes using list sampling with a ratio estimator. Standing tree carbon and down woody debris carbon were estimated across 10 broad forest types. LiDAR-derived gross total volume was used as a listing factor and big BAF samples to collect field data. Gross total volumes were “corrected” using a ratio estimator. The results show that standing tree carbon was 58.5 Mg C × ha-1 (± 2.9% SE), and dead woody debris carbon 1.8 Mg C × ha-1 (± 7.2% SE). With the exception of one forest type, these estimates were comparable to those derived from the carbon budget model of the Canadian forest sector (CBM-CFS3).
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Ortal, Patricia, and Masato Edahiro. "Similarity Measure for Product Attribute Estimation." IEEE Access 8 (2020): 179073–82. http://dx.doi.org/10.1109/access.2020.3027023.

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Dissertations / Theses on the topic "Attribute estimation"

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Azzeh, Mohammad Y. A. "Analogy-based software project effort estimation : contributions to projects similarity measurement, attribute selection and attribute weighting algorithms for analogy-based effort estimation." Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/4442.

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Software effort estimation by analogy is a viable alternative method to other estimation techniques, and in many cases, researchers found it outperformed other estimation methods in terms of accuracy and practitioners' acceptance. However, the overall performance of analogy based estimation depends on two major factors: similarity measure and attribute selection & weighting. Current similarity measures such as nearest neighborhood techniques have been criticized that have some inadequacies related to attributes relevancy, noise and uncertainty in addition to the problem of using categorical attributes. This research focuses on improving the efficiency and flexibility of analogy-based estimation to overcome the abovementioned inadequacies. Particularly, this thesis proposes two new approaches to model and handle uncertainty in similarity measurement method and most importantly to reflect the structure of dataset on similarity measurement using Fuzzy modeling based Fuzzy C-means algorithm. The first proposed approach called Fuzzy Grey Relational Analysis method employs combined techniques of Fuzzy set theory and Grey Relational Analysis to improve local and global similarity measure and tolerate imprecision associated with using different data types (Continuous and Categorical). The second proposed approach presents the use of Fuzzy numbers and its concepts to develop a practical yet efficient approach to support analogy-based systems especially at early phase of software development. Specifically, we propose a new similarity measure and adaptation technique based on Fuzzy numbers. We also propose a new attribute subset selection algorithm and attribute weighting technique based on the hypothesis of analogy-based estimation that assumes projects that are similar in terms of attribute value are also similar in terms of effort values, using row-wise Kendall rank correlation between similarity matrix based project effort values and similarity matrix based project attribute values. A literature review of related software engineering studies revealed that the existing attribute selection techniques (such as brute-force, heuristic algorithms) are restricted to the choice of performance indicators such as (Mean of Magnitude Relative Error and Prediction Performance Indicator) and computationally far more intensive. The proposed algorithms provide sound statistical basis and justification for their procedures. The performance figures of the proposed approaches have been evaluated using real industrial datasets. Results and conclusions from a series of comparative studies with conventional estimation by analogy approach using the available datasets are presented. The studies were also carried out to statistically investigate the significant differences between predictions generated by our approaches and those generated by the most popular techniques such as: conventional analogy estimation, neural network and stepwise regression. The results and conclusions indicate that the two proposed approaches have potential to deliver comparable, if not better, accuracy than the compared techniques. The results also found that Grey Relational Analysis tolerates the uncertainty associated with using different data types. As well as the original contributions within the thesis, a number of directions for further research are presented. Most chapters in this thesis have been disseminated in international journals and highly refereed conference proceedings.
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Thiyagarajah, Murali. "Attribute cardinality maps, new query result size estimation techniques for database systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0007/NQ42810.pdf.

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Thiyagarajah, Murali (Muralitharam) Carleton University Dissertation Computer Science. "Attribute cardinality maps; new query result size estimation techniques for database systems." Ottawa, 1999.

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Divelbiss, David L. "Evaluation of the Impact of Product Detail on the Accuracy of Cost Estimates." Ohio University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1127165055.

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Moser, Paolo 1985, Alexander Christian 1959 Vibrans, Ronald McRoberts, and Universidade Regional de Blumenau Programa de Pós-Graduação em Engenharia Ambiental. "Statistical and computational methods of forest attribute estimation and classification based on remotely sensed data." reponame:Biblioteca Digital de Teses e Dissertações FURB, 2018. http://www.bc.furb.br/docs/TE/2018/364705_1_1.pdf.

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Orientador: Alexander Christian Vibrans.
Coorientador: Ronald McRoberts.
Tese (Doutorado em Engenharia Ambiental) - Programa de Pós-Graduação em Engenharia Ambiental, Centro de Ciências Tecnológicas, Universidade Regional de Blumenau, Blumenau.
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FABBRI, MATTEO. "Sfruttare i Dati Sintetici per Migliorare la Comprensione del Comportamento Umano." Doctoral thesis, Università degli studi di Modena e Reggio Emilia, 2021. http://hdl.handle.net/11380/1239978.

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Le più recenti tecniche di Deep Learning richiedono enormi quantità di dati di addestramento per ottenere prestazioni simili a quelle umane. Soprattutto in Computer Vision, i Dataset sono costosi da creare in quanto richiedono uno sforzo manuale considerevole che non può essere automatizzato. Infatti, l'annotazione manuale è spesso soggetta ad errori, è incoerente per task soggettivi (ad es. age classification) e non è applicabile ad ogni tipo di dato (ad es. video ad elevato frame rate). Per alcuni task, come la pose estimation e il tracking, un'alternativa all'annotazione manuale implica l'utilizzo di sensori indossabili. Tuttavia, questo approccio non è praticabile in alcune circostanze (ad es. in scenari affollati), poiché la necessità di indossare tali sensori limita la sua applicazione ad ambienti controllati. Per superare questi limiti, abbiamo raccolto una serie di dati sintetici sfruttando un videogioco fotorealistico. Grazie all'utilizzo di un simulatore virtuale, le annotazioni sono prive di errori e sempre coerenti dato che non sono coinvolte operazioni manuali. Inoltre, i nostri dati sono adatti per applicazioni in-the-wild in quanto contengono un'elevata varietà di scenari e persone in ambienti non controllati. Tali dati sono conformi alle normative sulla privacy, in quanto nessun essere umano è stato coinvolto nell'acquisizione dei video. Sfruttando questi nuovi dati, sono stati condotti studi approfonditi su una serie di task. In particolare, per la pose estimation 2D e il tracking, abbiamo sviluppato un'architettura Deep che estrae congiuntamente i giunti delle persone e le associa su brevi intervalli temporali. Il nostro modello è in grado di ragionare esplicitamente riguardo a parti del corpo occluse, proponendo soluzioni plausibili di giunti non visibili. Per la pose estimation 3D, invece, abbiamo scelto di utilizzare heatmap volumetriche ad alta risoluzione per modellare le posizioni dei giunti, ideando un metodo di compressione semplice ed efficace per ridurre drasticamente le dimensioni di questa rappresentazione. Per l'attribute classification, abbiamo proposto una soluzione ad un problema comune nell'ambito della videosorveglianza, ovvero l'occlusione delle persone, progettando una rete neurale in grado di generare porzioni di persone occluse con un aspetto plausibile. Da un punto di vista pratico, abbiamo progettato un sistema di edge-AI in grado di valutare in tempo reale il rischio di contagio COVID-19 di un'area monitorata analizzando flussi video. Poiché i dati sintetici potrebbero essere suscettibili al domain-shift, abbiamo approfondito le tecniche di image-translation per head pose estimation, attribute recognition e face landmark localization.
Most recent Deep Learning techniques require large volumes of training data in order to achieve human-like performance. Especially in Computer Vision, datasets are expensive to create because they usually require a considerable manual effort that can not be automated. Indeed, manual annotation is error-prone, inconsistent for subjective tasks (e.g. age classification), and not applicable to particular data (e.g. high frame-rate videos). For some tasks, like pose estimation and tracking, an alternative to manual annotation implies the use of wearable sensors. However, this approach is not feasible under some circumstances (e.g. in crowded scenarios) since the need to wear sensors limits its application to controlled environments. To overcome all the aforementioned limitations, we collected a set of synthetic datasets exploiting a photorealistic videogame. By relying on a virtual simulator, the annotations are error-free and always consistent as there is no manual annotation involved. Moreover, our data is suitable for in-the-wild applications as it contains multiple scenarios and a high variety of people appearances. In addition, our datasets are privacy compliant as no real human was involved in the data acquisition. Leveraging this newly collected data, extensive studies have been conducted on a plethora of tasks. In particular, for 2D pose estimation and tracking, we propose a deep network architecture that jointly extracts people body parts and associates them across short temporal spans. Our model explicitly deals with occluded body parts, by hallucinating plausible solutions of not visible joints. For 3D pose estimation, we propose to use high-resolution volumetric heatmaps to model joint locations, devising a simple and effective compression method to drastically reduce the size of this representation. For attribute classification, we overcome a common problem in surveillance, namely people occlusion, by designing a network capable of hallucinating occluded people with a plausible aspect. From a more practical point of view, we design an edge-AI system capable of evaluating in real-time the COVID-19 contagion risk of a monitored area by analyzing video streams. As synthetic data might suffer domain-shift related problems, we further investigate image translation techniques for the tasks of head pose estimation, attribute recognition and face landmark localization.
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Park, Joonam. "Development and Application of Probabilistic Decision Support Framework for Seismic Rehabilitation of Structural Systems." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4898.

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Seismic rehabilitation of structural systems is an effective approach for reducing potential seismic losses such as social and economic losses. However, little or no effort has been made to develop a framework for making decisions on seismic rehabilitation of structural systems that systematically incorporates conflicting multiple criteria and uncertainties inherent in the seismic hazard and in the systems themselves. This study develops a decision support framework for seismic rehabilitation of structural systems incorporating uncertainties inherent in both the system and the seismic hazard, and demonstrates its application with detailed examples. The decision support framework developed utilizes the HAZUS method for a quick and extensive estimation of seismic losses associated with structural systems. The decision support framework allows consideration of multiple decision attributes associated with seismic losses, and multiple alternative seismic rehabilitation schemes represented by the objective performance level. Three multi-criteria decision models (MCDM) that are known to be effective for decision problems under uncertainty are employed and their applicability for decision analyses in seismic rehabilitation is investigated. These models are Equivalent Cost Analysis (ECA), Multi-Attribute Utility Theory (MAUT), and Joint Probability Decision Making (JPDM). Guidelines for selection of a MCDM that is appropriate for a given decision problem are provided to establish a flexible decision support system. The resulting decision support framework is applied to a test bed system that consists of six hospitals located in the Memphis, Tennessee, area to demonstrate its capabilities.
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Li, Gengxiang. "Rehaussement et détection des attributs sismiques 3D par techniques avancées d'analyse d'images." Phd thesis, Université Michel de Montaigne - Bordeaux III, 2012. http://tel.archives-ouvertes.fr/tel-00731886.

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Les Moments ont été largement utilisés dans la reconnaissance de formes et dans le traitement d'image. Dans cette thèse, nous concentrons notre attention sur les 3D moments orthogonaux de Gauss-Hermite, les moments invariants 2D et 3D de Gauss-Hermite, l'algorithme rapide de l'attribut de cohérence et les applications de l'interprétation sismique en utilisant la méthode des moments.Nous étudions les méthodes de suivi automatique d'horizon sismique à partir de moments de Gauss-Hermite en cas de 1D et de 3D. Nous introduisons une approche basée sur une étude multi-échelle des moments invariants. Les résultats expérimentaux montrent que la méthode des moments 3D de Gauss-Hermite est plus performante que les autres algorithmes populaires.Nous avons également abordé l'analyse des faciès sismiques basée sur les caractéristiques du vecteur à partir des moments 3D de Gauss -Hermite, et la méthode de Cartes Auto-organisatrices avec techniques de visualisation de données. L'excellent résultat de l'analyse des faciès montre que l'environnement intégré donne une meilleure performance dans l'interprétation de la structure des clusters.Enfin, nous introduisons le traitement parallèle et la visualisation de volume. En profitant des nouvelles performances par les technologies multi-threading et multi-cœurs dans le traitement et l'interprétation de données sismiques, nous calculons efficacement des attributs sismiques et nous suivons l'horizon. Nous discutons également l'algorithme de rendu de volume basé sur le moteur Open-Scene-Graph qui permet de mieux comprendre la structure de données sismiques.
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Tachfouti, Nabil. "Estimation de la mortalité attribuée au tabac au Maroc." Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0382/document.

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Introduction : Le tabac constitue la première cause de décès évitable dans le monde. Le Maroc constitue un bon modèle pour l’étude de la mortalité liée au tabagisme dans un pays en transition épidémiologique. Dans ce pays, les différentes études menées sur le tabagisme ont montré que sa prévalence chez les adultes a évolué de 17,2% en 2000 à 18,5% en 2006. Mais, peu de données existent sur les conséquences du tabac sur l’état de santé de la population Marocaine notamment en matière de décès prématurés. L’objectif de ce travail est d’estimer la mortalité globale liée au tabac au Maroc. Méthodes : Nous avons choisi le modèle SAMMEC (Smoking-Attributable Mortality, Morbidity, and Economic Cost) qui est une application conçue par les center of Disease Control (CDC). Le principe de cette méthode se base sur le calcul de la fraction attribuable au tabagisme (FAT) qui est la proportion des décès lié au tabac parmi l’ensemble des décès due à une maladie. Les données nécessaires pour cette modélisation sont : - Les risques relatifs (RR) de décès pour les fumeurs et les ex-fumeurs par rapport aux non- fumeurs. Ces RR ont été recueillis à partir de l’étude «American Cancer Society’s Cancer Prévention Study II (CPS-II)». -La fréquence de la consommation du tabac : les proportions des fumeurs, des anciens fumeurs et des non fumeurs ont été tirées à partir de l’étude MARTA; - Les causes de mortalité : il s’agit de 19 maladies liées au tabac regroupés en trois groupes de pathologies : les maladies cardio-vasculaires, les maladies de l’appareil respiratoire et les cancers. Ces données ont été recueillies à partir des déclarations de décès au niveau des bureaux communaux d’hygiène de la région de Casablanca durant l’année 2012. Elles ont été ensuite extrapolées sur la population Marocaine. Au terme du recueil, nous avons pu utiliser le modèle pour estimer la mortalité liée au tabac chez les personnes âgées de 35 ans et plus par sexe, et tranche d’âge.Résultats : La mortalité attribuable au tabac (MAT) durant l’année 2012 chez la population Marocaine âgée de 35 ans et plus est estimée à 4359 décès ; 3835 chez les hommes et 524 chez les femmes. La MAT représente 11,9% de la mortalité globale chez la tranche d’âge concernée par l’étude (personnes âgées de 35 ans et plus) ; 18,2% cher les hommes et 3,4 % chez les femmes. La MAT représente 66,4 % des décès par cause respiratoire, 53,9% de la mortalité par cancer et 13,7% des décès par maladies cardiovasculaires. La MAT est dominé par les décès par les cancers qui en représentent 48,4%, suivi des maladies cardiovasculaires qui en représentent 31,8% et celles de l’appareil respiratoire par 18,7%. Chez les hommes, les cancers représentent 49,8% de la MAT, les maladies cardiovasculaires en représentent 31,7% et celles de l’appareil respiratoire en représentent 18,5%. Chez les femmes, les cancers en représentent 38,5% suivi des maladies cardiovasculaires (31,8%) et celles de l’appareil respiratoire (29,7%). Discussion : Les chiffres alarmants du coût du tabagisme en termes de mortalité suggèrent l’urgence de sensibiliser davantage les décideurs politiques. Ces derniers seront menés à mettre en place une stratégie de lutte basée sur une politique prévention plus adaptée à cette situation épidémiologique et en mesure d’épargner un énorme fardeau au pays
Background : To establish the impact of tobacco smoking on mortality is essential to define and monitor public health interventions in developing countries. In Morocco, smoking prevalence has increased from 17.2% to 18.5% between 2000 and 2006. Moreover, no updated estimates are available on smoking attributable mortality (SAM). The aim of this study is to estimate the number of smoking attributable deaths in Morocco. Methods : The Smoking-Attributable Mortality, Morbidity and Economic Costs (SAMMEC) software was used to estimate the smoking attributable mortality for the year 2012. Smoking and ex-smoking prevalence’s of Moroccan’s aged 35 years or older were obtained from the national survey on tobacco “MARTA” data. Mortality data were drawn from the Mortality declaration registries in Casablanca region and extrapolated on Moroccan population. Results : Of total 36548 deaths recorded in Morocco in 2012 among person aged 35 years and older, 4359 were attributed to smoking in the three groups of selected causes; 3835 men’s and 524 women’s. Smoking accounted for 11.9% of all deaths; 18.3 % in men, and 3.4 % in women. Cancer was the most frequent cause, responsible for 50.7% (2112 deaths) of all smoking attributable deaths, followed by cardiovascular diseases (30.7%:1338 deaths) and respiratory diseases (19.6%: 864 deaths). Conclusion : Tobacco use caused one out of five male deaths. Four leading causes (lung cancer, ischemic heart disease, cerebrovascular disease and chronic airways obstruction) accounted for for 64.2% of all SAM; 65.0% among men and 61.6% among women’s. Overall, there is still a 5 high burden of tobacco-related deaths in Germany which leads to considerable costs for the German health system and economy. Effective and comprehensive actions must be taken in order to slow this epidemic in Morocco
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Hammoud, Wissam. "Attributes effecting software testing estimation; is organizational trust an issue?" Thesis, University of Phoenix, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3583478.

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This quantitative correlational research explored the potential association between the levels of organizational trust and the software testing estimation. This was conducted by exploring the relationships between organizational trust, tester’s expertise, organizational technology used, and the number of hours, number of testers, and time-coding estimated by the software testers. The research conducted on a software testing department of a health insurance organization, employed the use of the Organizational Trust Inventory- Short Form (OTI-SF) developed by Philip Bromiley and Larry Cummings and revealed a strong relationship between organizational trust and software testing estimation. The research reviews historical theories of organizational trust and include a deep discussion about software testing practices and software testing estimation. By examining the significant impact of organizational trust on project estimating and time-coding in this research, software testing leaders can benefit from this research to improve project planning and managing process by improving the levels of trust within their organizations.

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Books on the topic "Attribute estimation"

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United States. Federal Highway Administration. Office of Highway Information Management. and United States. Federal Highway Administration., eds. Special reports on trip and vehicle attributes: Based on data from the 1990 nationwide personal transportation survey (NPTS). [Washington, D.C.]: U.S. Dept. of Transportation, Federal Highway Administration, 1995.

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Pierson, Margaret Parker. Price competition and the impact of service attributes: Structural estimation and analytical characterizations of equilibrium behavior. [New York, N.Y.?]: [publisher not identified], 2012.

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Heckman, James J. Linear probability models of the demand for attributes with an empirical application to estimating the preferences of legislators. Cambridge, MA: National Bureau of Economic Research, 1996.

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Estimation of Product Attributes and Their Importances. Springer, 2012.

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Wallace, J. P., and A. Sherret. Estimation of Product Attributes and Their Importances. Springer London, Limited, 2012.

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Cronquist, Chapman. Estimation and Classification of Reserves of Crude Oil, Natural Gas, and Condensate. Society of Petroleum Engineers, 2001. http://dx.doi.org/10.2118/9781555630904.

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This book covers all aspects of estimating and classifying reserves of crude oil, natural gas, and condensate attributed to primary recovery mechanisms. Both deterministic and probabilistic procedures are discussed. Reserves definitions for many of the major producing countries are provided, including a comparison of the US Securities and Exchange Commission and Society of Petroleum Engineers–World Petroleum Congress reserves definitions. Case histories illustrate reasons for errors in reserves estimation. Correlation charts and empirical equations to estimate pressure/volume/temperature properties of reservoir fluids are provided in one of several special appendices.
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Ślusarski, Marek. Metody i modele oceny jakości danych przestrzennych. Publishing House of the University of Agriculture in Krakow, 2017. http://dx.doi.org/10.15576/978-83-66602-30-4.

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The quality of data collected in official spatial databases is crucial in making strategic decisions as well as in the implementation of planning and design works. Awareness of the level of the quality of these data is also important for individual users of official spatial data. The author presents methods and models of description and evaluation of the quality of spatial data collected in public registers. Data describing the space in the highest degree of detail, which are collected in three databases: land and buildings registry (EGiB), geodetic registry of the land infrastructure network (GESUT) and in database of topographic objects (BDOT500) were analyzed. The results of the research concerned selected aspects of activities in terms of the spatial data quality. These activities include: the assessment of the accuracy of data collected in official spatial databases; determination of the uncertainty of the area of registry parcels, analysis of the risk of damage to the underground infrastructure network due to the quality of spatial data, construction of the quality model of data collected in official databases and visualization of the phenomenon of uncertainty in spatial data. The evaluation of the accuracy of data collected in official, large-scale spatial databases was based on a representative sample of data. The test sample was a set of deviations of coordinates with three variables dX, dY and Dl – deviations from the X and Y coordinates and the length of the point offset vector of the test sample in relation to its position recognized as a faultless. The compatibility of empirical data accuracy distributions with models (theoretical distributions of random variables) was investigated and also the accuracy of the spatial data has been assessed by means of the methods resistant to the outliers. In the process of determination of the accuracy of spatial data collected in public registers, the author’s solution was used – resistant method of the relative frequency. Weight functions, which modify (to varying degree) the sizes of the vectors Dl – the lengths of the points offset vector of the test sample in relation to their position recognized as a faultless were proposed. From the scope of the uncertainty of estimation of the area of registry parcels the impact of the errors of the geodetic network points was determined (points of reference and of the higher class networks) and the effect of the correlation between the coordinates of the same point on the accuracy of the determined plot area. The scope of the correction was determined (in EGiB database) of the plots area, calculated on the basis of re-measurements, performed using equivalent techniques (in terms of accuracy). The analysis of the risk of damage to the underground infrastructure network due to the low quality of spatial data is another research topic presented in the paper. Three main factors have been identified that influence the value of this risk: incompleteness of spatial data sets and insufficient accuracy of determination of the horizontal and vertical position of underground infrastructure. A method for estimation of the project risk has been developed (quantitative and qualitative) and the author’s risk estimation technique, based on the idea of fuzzy logic was proposed. Maps (2D and 3D) of the risk of damage to the underground infrastructure network were developed in the form of large-scale thematic maps, presenting the design risk in qualitative and quantitative form. The data quality model is a set of rules used to describe the quality of these data sets. The model that has been proposed defines a standardized approach for assessing and reporting the quality of EGiB, GESUT and BDOT500 spatial data bases. Quantitative and qualitative rules (automatic, office and field) of data sets control were defined. The minimum sample size and the number of eligible nonconformities in random samples were determined. The data quality elements were described using the following descriptors: range, measure, result, and type and unit of value. Data quality studies were performed according to the users needs. The values of impact weights were determined by the hierarchical analytical process method (AHP). The harmonization of conceptual models of EGiB, GESUT and BDOT500 databases with BDOT10k database was analysed too. It was found that the downloading and supplying of the information in BDOT10k creation and update processes from the analyzed registers are limited. An effective approach to providing spatial data sets users with information concerning data uncertainty are cartographic visualization techniques. Based on the author’s own experience and research works on the quality of official spatial database data examination, the set of methods for visualization of the uncertainty of data bases EGiB, GESUT and BDOT500 was defined. This set includes visualization techniques designed to present three types of uncertainty: location, attribute values and time. Uncertainty of the position was defined (for surface, line, and point objects) using several (three to five) visual variables. Uncertainty of attribute values and time uncertainty, describing (for example) completeness or timeliness of sets, are presented by means of three graphical variables. The research problems presented in the paper are of cognitive and application importance. They indicate on the possibility of effective evaluation of the quality of spatial data collected in public registers and may be an important element of the expert system.
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Book chapters on the topic "Attribute estimation"

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Błaszczyński, Jerzy, Roman Słowiński, and Robert Susmaga. "Rule-Based Estimation of Attribute Relevance." In Rough Sets and Knowledge Technology, 36–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24425-4_7.

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Nodari, Angelo, Marco Vanetti, and Ignazio Gallo. "Visual Attribute Extraction Using Human Pose Estimation." In Pattern Recognition and Image Analysis, 350–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38628-2_41.

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Deng, Zeyuan, Yuchun Fang, and Yaofang Zhang. "Face Attribute Estimation with HMAX-GCNet Model." In Biometric Recognition, 392–99. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86608-2_43.

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Lee, K. C., J. S. Park, Y. S. Kim, and Y. T. Byun. "Missing Value Estimation Based on Dynamic Attribute Selection." In Knowledge Discovery and Data Mining. Current Issues and New Applications, 134–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-45571-x_15.

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Mariel, Petr, David Hoyos, Jürgen Meyerhoff, Mikolaj Czajkowski, Thijs Dekker, Klaus Glenk, Jette Bredahl Jacobsen, et al. "Econometric Modelling: Basics." In Environmental Valuation with Discrete Choice Experiments, 61–81. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62669-3_5.

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AbstractThis chapter addresses basic topics related to choice data analysis. It starts by describing the coding of attribute levels and choosing the functional form of the attributes in the utility function. Next, it focuses on econometric models with special attention devoted to the random parameter mixed logit model. In this context, the chapter compares different coefficient distributions to be used, addresses specifics of the cost attribute coefficient and it pays attention to potential correlations between random coefficients. Finally, topics related to the estimation procedure such as assuring its convergence or random draws are discussed.
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Gong, Sixue, Xiaoming Liu, and Anil K. Jain. "Jointly De-Biasing Face Recognition and Demographic Attribute Estimation." In Computer Vision – ECCV 2020, 330–47. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58526-6_20.

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Zhang, Weipeng, Jie Shen, Guangcan Liu, and Yong Yu. "A Latent Clothing Attribute Approach for Human Pose Estimation." In Computer Vision -- ACCV 2014, 146–61. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16865-4_10.

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Halford, Max, Philippe Saint-Pierre, and Franck Morvan. "Selectivity Estimation with Attribute Value Dependencies Using Linked Bayesian Networks." In Lecture Notes in Computer Science, 154–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-62386-2_6.

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Sosa-León, Sonia, Julio Waissman, José A. Olivas, and Manuel E. Prieto. "Estimation of Skill Level in Intelligent Tutoring Systems Using a Multi-attribute Methodology." In Communications in Computer and Information Science, 259–69. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03763-5_22.

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Egger, Bernhard, Sandro Schönborn, Andreas Forster, and Thomas Vetter. "Pose Normalization for Eye Gaze Estimation and Facial Attribute Description from Still Images." In Lecture Notes in Computer Science, 317–27. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11752-2_25.

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Conference papers on the topic "Attribute estimation"

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McCusker, James R., and Kourosh Danai. "Integrating Parameter Estimation Solutions From the Time and Time-Scale Domains." In ASME 2009 Dynamic Systems and Control Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/dscc2009-2552.

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A method of parameter estimation was recently introduced that separately estimates each parameter of the dynamic model [1]. In this method, regions coined as parameter signatures, are identified in the time-scale domain wherein the prediction error can be attributed to the error of a single model parameter. Based on these single-parameter associations, individual model parameters can then be estimated for iterative estimation. Relative to nonlinear least squares, the proposed Parameter Signature Isolation Method (PARSIM) has two distinct attributes. One attribute of PARSIM is to leave the estimation of a parameter dormant when a parameter signature cannot be extracted for it. Another attribute is independence from the contour of the prediction error. The first attribute could cause erroneous parameter estimates, when the parameters are not adapted continually. The second attribute, on the other hand, can provide a safeguard against local minima entrapments. These attributes motivate integrating PARSIM with a method, like nonlinear least-squares, that is less prone to dormancy of parameter estimates. The paper demonstrates the merit of the proposed integrated approach in application to a difficult estimation problem.
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F. da Costa, E., A. P. Grell, F. S. Moraes, and L. G. C. L. Loures. "Porosity Volume Attribute by Bayesian Estimation." In 68th EAGE Conference and Exhibition incorporating SPE EUROPEC 2006. European Association of Geoscientists & Engineers, 2006. http://dx.doi.org/10.3997/2214-4609.201402265.

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Trawick, David J., Philip C. Du Toit, Randy C. Paffenroth, and Gregory J. Norgard. "Ambiguous data association and entangled attribute estimation." In SPIE Defense, Security, and Sensing. SPIE, 2012. http://dx.doi.org/10.1117/12.920457.

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Niaki, S. T. A., and M. Khedmati. "Change point estimation in multi-attribute processes." In 2011 IEEE International Conference on Quality and Reliability (ICQR). IEEE, 2011. http://dx.doi.org/10.1109/icqr.2011.6031606.

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F. Jones, I., H. Baud, and A. Strachan. "Velocity as an Attribute - Continious Velocity Estimation from PreSDM CRP Gathers." In EAGE/SEG Workshop - Depth Imaging of Reservoir Attributes. European Association of Geoscientists & Engineers, 1998. http://dx.doi.org/10.3997/2214-4609.201406701.

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Xue, D., S. Y. Cheing, and P. Gu. "Design for Project Change Management: Part 2 — Attribute Design." In ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/detc2004-57332.

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This research introduces a new systematic approach to identify the optimal design configuration and attributes to minimize the potential construction project changes. The second part of this paper focuses on the attribute design aspect. In this research, the potential changes of design attribute values are modeled by probability distribution functions. Attribute values of the design whose construction tasks are least sensitive to the changes of these attribute values are identified based upon Taguchi Method. In addition, estimation of the potential project change cost due to the potential design attribute value changes is also discussed. Case studies in pipeline engineering design and construction have been conducted to show the effectiveness of the introduced approach.
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Park, Hosung, and Sue Moon. "Sampling bias in user attribute estimation of OSNs." In the 22nd International Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2487788.2487880.

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Xie, Yujiang, Yan Yang, and Dirk Gajewski. "Wavefront-attribute estimation for 3D laterally heterogeneous media." In SEG Technical Program Expanded Abstracts 2018. Society of Exploration Geophysicists, 2018. http://dx.doi.org/10.1190/segam2018-2996229.1.

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Pivot, F., and M. Bouayad. "Robust Estimation of Uncertainties of AVO Attribute Anomalies." In 82nd EAGE Annual Conference & Exhibition. European Association of Geoscientists & Engineers, 2020. http://dx.doi.org/10.3997/2214-4609.202010637.

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Huang, Shun-liang, Guan-yu Zhang, Ling Zhang, and Kai-quan Shi. "Attribute Composition Distribution and Rough Law Status Estimation." In 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD). IEEE, 2008. http://dx.doi.org/10.1109/fskd.2008.216.

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Reports on the topic "Attribute estimation"

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Mattingly, J. K. Plutonium Attribute Estimation From Passive NMIS Measurements at VNIIEF. Office of Scientific and Technical Information (OSTI), January 2002. http://dx.doi.org/10.2172/814039.

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Bradford, John, Scott B. Smithson, and Stephen Holbrook. Material Property Estimation for Direct Detection of DNAPL using Integrated Ground-Penetrating Radar Velocity, Imaging and Attribute Analysis. Office of Scientific and Technical Information (OSTI), June 2001. http://dx.doi.org/10.2172/833499.

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Bradford, John, Scott B. Smithson, and W. Stephen Holbrook. Material Property Estimation for Direct Detection of DNAPL using Integrated Ground-Penetrating Radar Velocity, Imaging and Attribute Analysis. Office of Scientific and Technical Information (OSTI), June 2003. http://dx.doi.org/10.2172/833501.

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John H. Bradford, Stephen Holbrook, and Scott B. Smithson. Material Property Estimation for Direct Detection of DNAPL using Integrated Ground-Penetrating Radar Velocity, Imaging and Attribute Analysis. Office of Scientific and Technical Information (OSTI), December 2004. http://dx.doi.org/10.2172/835736.

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Bradford, John, Scott B. Smithson, and W. Stephen Holbrook. Material Property Estimation for Direct Detections of DNAPL using Integrated Ground-Penetrating Radar Velocity, Imaging and Attribute Analysis. Office of Scientific and Technical Information (OSTI), June 2004. http://dx.doi.org/10.2172/838766.

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Bradford, John H., W. Stephen Holbrook, and Scott B. Smithson. Material Property Estimation for Direct Detection of DNAPL using Integrated Ground-Penetrating Radar Velocity, Imaging and Attribute Analysis. Office of Scientific and Technical Information (OSTI), December 2004. http://dx.doi.org/10.2172/839383.

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Conrad, Ryan. Methods for Estimating Vehicle Fuel Consumption in Urban Road Networks Using Geographical Attributes. Portland State University, August 2018. http://dx.doi.org/10.15760/ccemp.42.

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Dillon, Michael B., and Staci R. Kane. Estimating Fallout Building Attributes from Architectural Features and Global Earthquake Model (GEM) Building Descriptions. Office of Scientific and Technical Information (OSTI), March 2017. http://dx.doi.org/10.2172/1361602.

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Golan, Amos, and Tanja F. Blackstone. Estimating Promotion Probabilities of Navy Officers Based on Individual's Attributes and Other Global Effects. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada565167.

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mattingly, j. k., j. t. mihalczo, j. a. mullens, r. b. perez, and t. e. valentine. Estimating Attributes of Nuclear Weapon and Other Fissile Material Configuration Using Features Of Nuclear Materials Identification Signatures. Office of Scientific and Technical Information (OSTI), August 1999. http://dx.doi.org/10.2172/12462.

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