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Academic literature on the topic 'Consumers Classification Computer programs'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Consumers Classification Computer programs"

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ZHU, JINGBO, MATTHEW Y. MA, JINHONG K. GUO, and ZHENXING WANG. "CONTENT CLASSIFICATION AND RECOMMENDATION TECHNIQUES FOR VIEWING ELECTRONIC PROGRAMMING GUIDE ON A PORTABLE DEVICE." International Journal of Pattern Recognition and Artificial Intelligence 21, no. 02 (March 2007): 375–95. http://dx.doi.org/10.1142/s0218001407005399.

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With the merge of digital television (DTV) and the exponential growth of broadcasting network, an overwhelmingly amount of information has been made available to a consumer's home. Therefore, how to provide consumers with the right amount of information becomes a challenging problem. In this paper, we propose an electronic programming guide (EPG) recommender based on natural language processing techniques, more specifically, text classification. This recommender has been implemented as a service on a home network that facilitates the personalized browsing and recommendation of TV programs on a portable remote device. Evaluations of our Maximum Entropy text classifier were performed on multiple categories of TV programs, and a near 80% retrieval rate is achieved using a small set of training data.
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Abreu-Lima, C., P. Arnaud, C. R. Brohet, B. Denis, J. Gehring, I. Graham, G. van Herpen, et al. "Evaluation of ECG Interpretation Results Obtained by Computer and Cardiologists." Methods of Information in Medicine 29, no. 04 (1990): 308–16. http://dx.doi.org/10.1055/s-0038-1634794.

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AbstractIn an international project investigators from 25 institutes are trying to establish a common reference library and evaluation methods for testing the diagnostic performance of various ECG computer programs and of cardiologists, based on ECG-independent clinical information. A first set of 500 validated ECGs was collected and analyzed by fifteen different computer programs and nine cardiologists, seven of who analysed the ECG and five the VCG. A coding scheme was used to map individual diagnostic statements onto a common set. Combined program and referee results were obtained by weighted averaging. Preliminary results indicate that the classification accuracy of several programs can still be improved. However, it was also apparent that the results of the best 12-lead ECG computer programs proved to be almost as accurate as the best of seven cardiologists in classifying seven main disease categories, i.e., normal, left, right and biventricular hypertrophy, anterior, inferior and combined myocardial infarction. Evaluation of rhythm statements and conduction disturbances was not included in the study. The data collection is still being pursued in order to reach over 1,000 cases. In this way a common diagnostic database is being established for comparative testing of diagnostic computer programs. This should lead to consumer protection and improve the accuracy and reliability of computerized electrocardiography.
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Kumar C, Udhaya, Miruthula R C, Pavithra G, Revathi R, and Suganya M. "FPGA-based Hardware Acceleration for Fruit Recognition Using SVM." Irish Interdisciplinary Journal of Science & Research 06, no. 02 (2022): 22–29. http://dx.doi.org/10.46759/iijsr.2022.6204.

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Selection classification for Fruit recognition could be an absolute zone of inspection. Fruit Recognition mistreatment FPGA-based Hardware Acceleration by SVM is helpful for the observance and indexing of the fruits consistent with their kind with the peace of mind of a quick production chain. During this test, we have processed to initial replacement prime quality data-set of pictures grouped in the 5 preferred varieties of oval-shaped fruits. Honor to the fast image process techniques for the development, image resolution, quality of the algorithms leads to carry-out image process and computational tasks. In recent years, deep neural networks have a diode to the event of the many new applications associated with preciseness agriculture, as well as fruit recognition. An algorithm consumes computer power and memory, which has a significant impact on standard and performance, especially when working with large image datasets. Within the planned work, FPG is A based mostly on hardware acceleration for fruit, and recognition is mistreatment with SVM. The Support Vector Machine could be a real-time machine learning tool meant for high predicted classification accuracy through the attributes mentioned. Using SVM for embedded system programs is incredibly difficult attributable to the intensive computations needed. This will increase the attractiveness of implementing SVM on hardware platforms for reaching performance computing with the demanded value of power consumption. Finally, a difficult trade-off between meeting embedded period systems constraints and high classification accuracy has been determined.
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Kumar C, Udhaya, Miruthula R C, Pavithra G, Revathi R, and Suganya M. "FPGA-based Hardware Acceleration for Fruit Recognition Using SVM." Irish Interdisciplinary Journal of Science & Research 06, no. 02 (2022): 22–29. http://dx.doi.org/10.46759/iijsr.2022.6204.

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Selection classification for Fruit recognition could be an absolute zone of inspection. Fruit Recognition mistreatment FPGA-based Hardware Acceleration by SVM is helpful for the observance and indexing of the fruits consistent with their kind with the peace of mind of a quick production chain. During this test, we have processed to initial replacement prime quality data-set of pictures grouped in the 5 preferred varieties of oval-shaped fruits. Honor to the fast image process techniques for the development, image resolution, quality of the algorithms leads to carry-out image process and computational tasks. In recent years, deep neural networks have a diode to the event of the many new applications associated with preciseness agriculture, as well as fruit recognition. An algorithm consumes computer power and memory, which has a significant impact on standard and performance, especially when working with large image datasets. Within the planned work, FPG is A based mostly on hardware acceleration for fruit, and recognition is mistreatment with SVM. The Support Vector Machine could be a real-time machine learning tool meant for high predicted classification accuracy through the attributes mentioned. Using SVM for embedded system programs is incredibly difficult attributable to the intensive computations needed. This will increase the attractiveness of implementing SVM on hardware platforms for reaching performance computing with the demanded value of power consumption. Finally, a difficult trade-off between meeting embedded period systems constraints and high classification accuracy has been determined.
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Chen, Wen-Kuo, Venkateswarlu Nalluri, Man-Li Lin, and Ching-Torng Lin. "Identifying Decisive Socio-Political Sustainability Barriers in the Supply Chain of Banking Sector in India: Causality Analysis Using ISM and MICMAC." Mathematics 9, no. 3 (January 26, 2021): 240. http://dx.doi.org/10.3390/math9030240.

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The banking sector often plays a crucial role in the improvement of infrastructure and economy of any country. In many emerging economies, it is apparent that a wide variety of social and political issues are related to the associated supply chain sustainability of financial service firms. Although such sustainability and its implementation issues have largely been addressed in existing research literature and in practice for many years, the attention towards socio-political sustainability aspects has been quite limited. Thus, this study attempted to explore the determinants for improving socio-political sustainability in financial service firms. Through adopting the fuzzy Delphi method (FDM), performing an exhaustive literature review, and conducting semi-structured interviews with the decision-makers of the service firms, nine key barriers for socio-political sustainability were first identified in this study. Then, the influence relationships of the key barriers were assessed by 15 experts. During the assessment process, the interrelationships and their dependence powers among key barriers were analyzed using the interpretive structural modelling (ISM) approach and cross-impact matrix multiplication applied to classification (MICMAC) methods. The assessment results show that among the studied barriers, “antisocial considerations”, “unstable political climate”, and “lack of political coherence” are the decisive barriers that affect the socio-political sustainability in the supply chain of financial service firms. The knowledge in understanding and reducing these decisive barriers can provide service sector practitioners, especially those with limited resources, the enhanced capability to conduct better planning and designing of effective and continuous improvement programs, so as to win over new consumers and retain existing clients by offering sustainable services.
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Hatalis, Kostas, Chengbo Zhao, Parv Venkitasubramaniam, Larry Snyder, Shalinee Kishore, and Rick S. Blum. "Modeling and Detection of Future Cyber-Enabled DSM Data Attacks." Energies 13, no. 17 (August 21, 2020): 4331. http://dx.doi.org/10.3390/en13174331.

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Demand-Side Management (DSM) is an essential tool to ensure power system reliability and stability. In future smart grids, certain portions of a customer’s load usage could be under the automatic control of a cyber-enabled DSM program, which selectively schedules loads as a function of electricity prices to improve power balance and grid stability. In this scenario, the security of DSM cyberinfrastructure will be critical as advanced metering infrastructure and communication systems are susceptible to cyber-attacks. Such attacks, in the form of false data injections, can manipulate customer load profiles and cause metering chaos and energy losses in the grid. The feedback mechanism between load management on the consumer side and dynamic price schemes employed by independent system operators can further exacerbate attacks. To study how this feedback mechanism may worsen attacks in future cyber-enabled DSM programs, we propose a novel mathematical framework for (i) modeling the nonlinear relationship between load management and real-time pricing, (ii) simulating residential load data and prices, (iii) creating cyber-attacks, and (iv) detecting said attacks. In this framework, we first develop time-series forecasts to model load demand and use them as inputs to an elasticity model for the price-demand relationship in the DSM loop. This work then investigates the behavior of such a feedback loop under intentional cyber-attacks. We simulate and examine load-price data under different DSM-participation levels with three types of random additive attacks: ramp, sudden, and point attacks. We conduct two investigations for the detection of DSM attacks. The first studies a supervised learning approach, with various classification models, and the second studies the performance of parametric and nonparametric change point detectors. Results conclude that higher amounts of DSM participation can exacerbate ramp and sudden attacks leading to better detection of such attacks, especially with supervised learning classifiers. We also find that nonparametric detection outperforms parametric for smaller user pools, and random point attacks are the hardest to detect with any method.
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Dalay, Jacobson B., and Fershie Yap. "CONSUMERS’ AWARENESS ON JOLLIBEE FOODS CORPORATION’S CORPORATE SOCIAL RESPONSIBILITY PROGRAMS AND THEIR BUYING BEHAVIOR TOWARDS A STRATEGIC CORPORATE SOCIAL RESPONSIBILITY." International Journal of Engineering Technologies and Management Research 8, no. 4 (April 14, 2021): 25–39. http://dx.doi.org/10.29121/ijetmr.v8.i4.2021.895.

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The research identified the consumers’ awareness of CSR, consumers’ buying behavior relating to Jollibee Foods Corporation’s (JFC) Corporate Social Responsibility (CSR) programs as well as to JFC as an organization, determined the relationship between consumers’ CSR awareness and consumer buying behavior, and ascertained differences in consumer buying behavior according to their socio-demographic classification. The study used descriptive research design, using self-administered questionnaires through purposive sampling method in the selection of respondents with a sample size of 250 consumers who participated in the survey. Data were statistically treated using mean, frequency, and percent distribution and standard deviation, chi-square, correlation, Kruskal-Wallis, and Mann-Whitney. Based on the findings, the researcher concludes that 25-34 years old consumers prefer Jollibee Foods brands as their fast-food preference. Females, those with Bachelor’s degrees, and are employed prefer JFC as well. The majority of respondents/consumers have knowledge on the topic at hand, thus they could be seen as the current audience of the CSR programs being done by JFC. It is highly commendable that JFC is conducting programs for the benefit of its targeted segments and communities, but consumers are not fully aware of these programs. Overall, consumers are most aware of other CSR programs done by JFC. Therefore, the researcher recommends creating a strategic CSR communication of JFC’s CSR programs to increase the awareness of consumers. It should capitalize on identified significant relationships between consumers’ CSR awareness and buying behavior to gain economic advantage.
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Ion, I., R. Arhire, and M. Macesanu. "Programs complexity: comparative analysis hierarchy, classification." ACM SIGPLAN Notices 22, no. 4 (April 1987): 94–102. http://dx.doi.org/10.1145/24714.24726.

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Dimitrieska, Savica, and Tanja Efremova. "LOYALTY PROGRAMS: DO COMPANIES REALLY MAKE CONSUMERS LOYAL?" Entrepreneurship 9, no. 2 (November 10, 2021): 23–32. http://dx.doi.org/10.37708/ep.swu.v9i2.2.

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In the markets of different products and services, the interests of both, companies and consumers collide. Companies that offer products and services expect a return on investment and higher profits. They can achieve these goals only if they have regular consumers, preferably loyal who will buy products and services more often or in larger quantities. The companies are interested in achieving long-term and sustainable relationships with the consumers and they want to minimize the churn and their switching to competitors. Consumers, on the other hand, have more sophisticated demands and expect more value for less money. They are interested not only in the quality of the product, but also in packaging, discounts, cashback, rewards, additional customer services, free shipping, maintenance, special treatments, reputation, etc. To meet these consumer expectations, companies offer many promotional activities, including loyalty programs. Loyalty programs, as part of the CRM (customer relationship management), are marketing programs that reward consumers for their repeated purchases over a longer period of time. Unlike other promotional tools, loyalty programs need to build a long-term relationship between companies and their consumers. But despite the offer of such programs, many studies show that consumers are not loyal and do not fully enjoy the benefits of the programs. Do companies give “something for nothing” and spend their money in vain? What are the reasons for the downfall of loyalty programs? This paper aims to investigate the reasons for consumer disloyalty despite the offered companies' loyalty programs. The paper will also provide guidance for companies to design loyalty programs that will attract more consumers.
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Shi, Yong, YingJie Tian, XiaoJun Chen, and Peng Zhang. "Regularized multiple criteria linear programs for classification." Science in China Series F: Information Sciences 52, no. 10 (October 2009): 1812–20. http://dx.doi.org/10.1007/s11432-009-0126-5.

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Dissertations / Theses on the topic "Consumers Classification Computer programs"

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Abdalla, Lena(Lena A. ). "Classification of computer programs in the Scratch online community." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129862.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2020
Cataloged from student-submitted PDF of thesis.
Includes bibliographical references (pages 133-136).
Scratch is a graphical programming platform that empowers children to create computer programs and realize their ideas. Although the Scratch online community is filled with a variety of diverse projects, many of these projects also share similarities. For example, they tend to fall into certain categories, including games, animations, stories, and more. Throughout this thesis, I describe the application of Natural Language Processing (NLP) techniques to vectorize and classify Scratch projects by type. This effort included constructing a labeled dataset of 873 Scratch projects and their corresponding types, to be used for training a supervised classifier model. This dataset was constructed through a collective process of consensus-based annotation by experts. To realize the goal of classifying Scratch projects by type, I first train an unsupervised model of meaningful vector representations for Scratch blocks based on the composition of 500,000 projects. Using the unsupervised model as a basis for representing Scratch blocks, I then train a supervised classifier model that categorizes Scratch projects by type into one of: "animation", "game", and "other". After an extensive hyperparameter tuning process, I am able to train a classifier model with an F1 Score of 0.737. I include in this paper an in-depth analysis of the unsupervised and supervised models, and explore the different elements that were learned during training. Overall, I demonstrate that NLP techniques can be used in the classification of computer programs to a reasonable level of accuracy.
by Lena Abdalla.
M. Eng.
M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
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Shahzad, Raja Muhammad Khurram. "Classification of Potentially Unwanted Programs Using Supervised Learning." Licentiate thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00548.

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Malicious software authors have shifted their focus from illegal and clearly malicious software to potentially unwanted programs (PUPs) to earn revenue. PUPs blur the border between legitimate and illegitimate programs and thus fall into a grey zone. Existing anti-virus and anti-spyware software are in many instances unable to detect previously unseen or zero-day attacks and separate PUPs from legitimate software. Many tools also require frequent updates to be effective. By predicting the class of particular piece of software, users can get support before taking the decision to install the software. This Licentiate thesis introduces approaches to distinguish PUP from legitimate software based on the supervised learning of file features represented as n-grams. The overall research method applied in this thesis is experiments. For these experiments, malicious software applications were obtained from anti-malware industrial partners. The legitimate software applications were collected from various online repositories. The general steps of supervised learning, from data preparation (n-gram generation) to evaluation were, followed. Different data representations, such as byte codes and operation codes, with different configurations, such as fixed-size, variable-length, and overlap, were investigated to generate different n-gram sizes. The experimental variables were controlled to measure the correlation between n-gram size, the number of features required for optimal training, and classifier performance. The thesis results suggest that, despite the subtle difference between legitimate software and PUP, this type of software can be classified accurately with a low false positive and false negative rate. The thesis results further suggest an optimal size of operation code-based n-grams for data representation. Finally, the results indicate that classification accuracy can be increased by using a customized ensemble learner that makes use of multiple representations of the data set. The investigated approaches can be implemented as a software tool with a less frequently required update in comparison to existing commercial tools.
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Torri, Stephen A. Hamilton John A. "Generic reverse engineering architecture with compiler and compression classification components." Auburn, Ala, 2009. http://hdl.handle.net/10415/1583.

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Janidlo, Peter S. "Rule-based expert systems and tonal chord classification." Virtual Press, 1999. http://liblink.bsu.edu/uhtbin/catkey/1137841.

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The purpose of the proposed thesis is to:1. Define expert systems and discuss various implementation techniques for the components of expert systems. This includes discussion on knowledge representation, inference methods, methods for dealing with uncertainty, and methods of explanation. Specifically, the focus will be on the implementation of rule-based expert systems;2. Apply selected expert system techniques to a case study. The case study will be a rule-based expert system in Prolog to recognize and identify musical chords from tonal harmony. The system will have a general knowledge base containing fundamental rules about chord construction. It will also contain some knowledge that will allow it to deduce non-trivial chords. Furthermore, it will contain procedures to deal with uncertainty and explanation;3. Explain general concepts about music theory and tonal chord classification to put the case study in context; and4. Discuss the limitations of expert systems based on the results of the case study and the current literature.
Department of Computer Science
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Pester, Matthias. "Visualization Tools for 2D and 3D Finite Element Programs - User's Manual." Universitätsbibliothek Chemnitz, 2006. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200600436.

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This paper deals with the visualization of numerical results as a very convenient method to understand and evaluate a solution which has been calculated as a set of millions of numerical values. One of the central research fields of the Chemnitz SFB 393 is the analysis of parallel numerical algorithms for large systems of linear equations arising from differential equations (e.g. in solid and fluid mechanics). Solving large problems on massively parallel computers makes it more and more impossible to store numerical data from the distributed memory of the parallel computer to the disk for later postprocessing. However, the developer of algorithms is interested in an on-line response of his algorithms. Both visual and numerical response of the running program may be evaluated by the user for a decision how to switch or adjust interactively certain parameters that may influence the solution process. The paper gives a survey of current programmer and user interfaces that are used in our various 2D and 3D parallel finite element programs for the visualization of the solution.
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Kim, Kye Hyun 1956. "Classification of environmental hydrologic behaviors in Northeastern United States." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/277083.

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Environmental response to acidic deposition occurs through the vehicle of water movement in the ecosystem. As a part of the environmental studies for acidic deposition in the ecosystem, output-based hydrologic classification was done from basin hydrologies based on the distribution of the baseflow, snowmelt, and the direct runoff sources. Because of the differences in the flow paths and exposure duration, those components were assumed to represent distinct geochemical responses. As a first step, user-friendly software has been developed to calculate the baseflow based on the separation of annual hydrographs. It also generates the hydrograph for visual analysis using trial separation slope. After the software was completed, about 1200 stream flow gauging stations in Northeastern U.S. were accessed for flow separation and other hydrologic characteristics. At the final stage, based on the output from the streamflow analysis, cluster analysis was performed to classify the streamflow behaviors in terms of acidic inflow. The output from the cluster analysis shows more efficient regional boundaries of the subregions than the current regional boundaries used by U.S. Environmental Protection Agency (U.S.E.P.A.) for the environmental management in terms of acidic deposition based on the regional baseflow properties.
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Sun, Hongliang, and University of Lethbridge Faculty of Arts and Science. "Implementation of a classification algorithm for institutional analysis." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Arts and Science, 2008, 2008. http://hdl.handle.net/10133/738.

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The report presents an implemention of a classification algorithm for the Institutional Analysis Project. The algorithm used in this project is the decision tree classification algorithm which uses a gain ratio attribute selectionmethod. The algorithm discovers the hidden rules from the student records, which are used to predict whether or not other students are at risk of dropping out. It is shown that special rules exist in different data sets, each with their natural hidden knowledge. In other words, the rules that are obtained depend on the data that is used for classification. In our preliminary experiments, we show that between 55-78 percent of data with unknown class lables can be correctly classified, using the rules obtained from data whose class labels are known. We feel this is acceptable, given the large number of records, attributes, and attribute values that are used in the experiments. The project results are useful for large data set analysis.
viii, 38 leaves ; 29 cm. --
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Klinka, Karel, Pal Varga, and Christine Chourmouzis. "Select CD : computer support system for making tree species and reproduction cutting decisions in the coastal forest of BC." Forest Sciences Department, University of British Columbia, 1999. http://hdl.handle.net/2429/672.

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"SELECT CD is a site-specific, decision-support tool for selecting ecologically viable tree species, reproduction cuttings, and regeneration methods in the coastal forest (CDF, CWH, and MH zones). SELECT CD integrates information from several existing guides with new information from literature and recent research into a single, user-friendly resource. SELECT CD also includes a rich library of visuals and an illustrated glossary of technical terms."
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Riss, Joëlle. "Principes de stéréologie des formes en pétrographie quantitative." Orléans, 1988. http://www.theses.fr/1988ORLE2015.

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Les différentes populations de granis des agrégats polycristallins monominéraux déformés et cristallises sont classés suivant leur forme d'après le diagramme de blaschke. On étudie les polyèdres trivalents à 13 et 14 faces grâces a un logiciel de calcul des coordonnées des sommets. On peut aussi déduire les caractéristiques d'un polyèdre a partir de ses coordonnées ainsi que des simulations numériques d'intercepts linéaires et planauss du polyèdre isole et de l'agrégat qu'il engendre s'il est empilable
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Jagarlapudi, Saketha Nath. "Learning Algorithms Using Chance-Constrained Programs." Thesis, 2008. http://hdl.handle.net/2005/733.

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This thesis explores Chance-Constrained Programming (CCP) in the context of learning. It is shown that chance-constraint approaches lead to improved algorithms for three important learning problems — classification with specified error rates, large dataset classification and Ordinal Regression (OR). Using moments of training data, the CCPs are posed as Second Order Cone Programs (SOCPs). Novel iterative algorithms for solving the resulting SOCPs are also derived. Borrowing ideas from robust optimization theory, the proposed formulations are made robust to moment estimation errors. A maximum margin classifier with specified false positive and false negative rates is derived. The key idea is to employ chance-constraints for each class which imply that the actual misclassification rates do not exceed the specified. The formulation is applied to the case of biased classification. The problems of large dataset classification and ordinal regression are addressed by deriving formulations which employ chance-constraints for clusters in training data rather than constraints for each data point. Since the number of clusters can be substantially smaller than the number of data points, the resulting formulation size and number of inequalities are very small. Hence the formulations scale well to large datasets. The scalable classification and OR formulations are extended to feature spaces and the kernelized duals turn out to be instances of SOCPs with a single cone constraint. Exploiting this speciality, fast iterative solvers which outperform generic SOCP solvers, are proposed. Compared to state-of-the-art learners, the proposed algorithms achieve a speed up as high as 10000 times, when the specialized SOCP solvers are employed. The proposed formulations involve second order moments of data and hence are susceptible to moment estimation errors. A generic way of making the formulations robust to such estimation errors is illustrated. Two novel confidence sets for moments are derived and it is shown that when either of the confidence sets are employed, the robust formulations also yield SOCPs.
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Books on the topic "Consumers Classification Computer programs"

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Christian, Müller, ed. Speaker classification. Berlin: Springer, 2007.

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Padilla, Juan A. Cognos 8 BI for consumers: A step-by-step introductory guide to Cognos Connection. Guaynabo, PR: Technology Partners Books, 2007.

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Elias, Peter. Computer assisted standard occupational coding. London: H.M.S.O., 1993.

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Orlóci, László. Conapack: Program for canonical analysis of classification tables. The Hague, Netherlands: SPB Academic, 1992.

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Dewey for Windows guide: Records, searching, and number building. Albany, N.Y: Forest Press, 1998.

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Power, Christopher. The Mobile Movie Database: An experiment in location context accuracy. London, ON: Dept. of Computer Science, University of Western Ontario, 2004.

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Power, Christopher. The mobile movie database: An experiment in location context accuracy. London, Ont: Dept. of Computer Science, University of Western Ontario, 2003.

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Mortensen, Dennis R. Yahoo! Web Analytics. New York: John Wiley & Sons, Ltd., 2009.

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Yahoo! Web analytics: Tracking, reporting, and analyzing for data-driven insights. Indianapolis, Ind: Wiley Technology Pub., 2009.

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Food and Agriculture Organization of the United Nations., ed. The European soil information system: Proceedings of a Technical Consultation, Rome, Italy, 2-3 September 1999. Rome: Food and Agriculture Organization of the United Nations, 2000.

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Book chapters on the topic "Consumers Classification Computer programs"

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Jirapanthong, Waraporn, Winyu Niranatlamphong, and Karuna Yampray. "Applying a Classification Model for Selecting Postgraduate Programs." In Lecture Notes in Computer Science, 330–37. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61833-3_35.

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Goodall, D. W., P. Ganis, and E. Feoli. "Probabilistic Methods in Classification: A Manual for Seven Computer Programs." In Computer assisted vegetation analysis, 453–67. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3418-7_40.

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Sun, Fei, Ding-Bang Luh, Yulin Zhao, and Yue Sun. "Study on the Deep Learning Product Classification Based on the Motivation of Consumers." In Communications in Computer and Information Science, 537–45. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06391-6_66.

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Huamán, Baldwin, Dante Gómez, Danny Lévano, Miguel Valles-Coral, Jorge Raul Navarro-Cabrera, and Lloy Pinedo. "Classification Model Based on Chatbot and Unsupervised Algorithms to Determine Psychological Intervention Programs in Peruvian University Students." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 191–203. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-22324-2_15.

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Sackin, M. J. "11 Computer Programs for Classification and Identification." In Methods in Microbiology, 459–94. Elsevier, 1988. http://dx.doi.org/10.1016/s0580-9517(08)70417-3.

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Helal, Guida, and Wilson Ozuem. "Social Media and Social Identity in the Millennial Generation." In Leveraging Computer-Mediated Marketing Environments, 43–82. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7344-9.ch003.

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The active presence of fashion brands online serves as a channel for customers to connect with brands for different intentions. This connection acts as an outlet customers employ in furthering social identity through brand associations. Brand perceptions are accordingly formed among consumers based on the promised functional and symbolic benefits consumption of that brand guarantees. Social media has assumed an integral role in fostering brand-customer relationships that ultimately augment social identity. The following chapter examines the role social media has played on brand perceptions in the fashion apparel and accessories industry from a social identity theory perspective. The chapter focuses on theoretical implications and managerial implications. The concluding section offers some significant roles that social media and social identity may play in keeping up with the design and development of marketing communications programs.
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Blasco, J., N. Aleixos, S. Cubero, F. Albert, D. Lorente, and J. Gómez-Sanchis. "In-line Sorting of Processed Fruit Using Computer Vision." In Intelligent Data Analysis for Real-Life Applications, 124–45. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-4666-1806-0.ch007.

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Nowadays, there is a growing demand for quality fruits and vegetables that are simple to prepare and consume, like minimally processed fruits. These products have to accomplish some particular characteristics to make them more attractive to the consumers, like a similar appearance and the total absence of external defects. Although recent advances in machine vision have allowed for the automatic inspection of fresh fruit and vegetables, there are no commercially available equipments for sorting of minority processed fruits, like arils of pomegranate (Punica granatum L) or segments of Satsuma mandarin (Citrus unshiu) ready to eat. This work describes a complete solution based on machine vision for the automatic inspection and classification of these fruits based on their estimated quality. The classification is based on morphological and colour features estimated from images taken in-line, and their analysis using statistical methods in order to grade the fruit into commercial categories.
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Olmo, Juan Luis, José Raúl Romero, and Sebastián Ventura. "Ant Programming Algorithms for Classification." In Advances in Data Mining and Database Management, 107–28. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6078-6.ch005.

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Ant programming is a kind of automatic programming that generates computer programs by using the ant colony metaheuristic as the search technique. It has demonstrated good generalization ability for the extraction of comprehensible classifiers. To date, three ant programming algorithms for classification rule mining have been proposed in the literature: two of them are devoted to regular classification, differing mainly in the optimization approach, single-objective or multi-objective, while the third one is focused on imbalanced domains. This chapter collects these algorithms, presenting different experimental studies that confirm the aptitude of this metaheuristic to address this data-mining task.
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Gardner-McCune, Christina, and Yerika Jimenez. "Historical App Developers." In Advances in Educational Marketing, Administration, and Leadership, 85–112. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2005-4.ch005.

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Unlike enrollment in undergraduate computer science degree programs, there are no gender or ethnic imbalances in K?12 enrollment. This chapter discusses an approach to broadening minority participation in computing through the integration of computer science (CS) into history courses. It presents an alignment between computational thinking and historical thinking that makes history courses an attractive fit for CS integration. It also presents a project-based approach using MIT App Inventor that leverages students' interests in mobile technology to facilitate the creation of historical mobile applications. This chapter outlines key findings from a two-year study on integrating cross-disciplinary curricula into history courses and the impact on minority students as they become knowledge, artifact, and technology producers rather than mere consumers.
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Panda, Mrutyunjaya, and Ahmad Taher Azar. "Hybrid Multi-Objective Grey Wolf Search Optimizer and Machine Learning Approach for Software Bug Prediction." In Advances in Systems Analysis, Software Engineering, and High Performance Computing, 314–37. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5788-4.ch013.

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Software bugs (or malfunctions) pose a serious threat to software developers with many known and unknown bugs that may be vulnerable to computer systems, demanding new methods, analysis, and techniques for efficient bug detection and repair of new unseen programs at a later stage. This chapter uses evolutionary grey wolf (GW) search optimization as a feature selection technique to improve classifier efficiency. It is also envisaged that software error detection would consider the nature of the error when repairing it for remedial action instead of simply finding it either faulty or non-defective. To address this problem, the authors use bug severity multi-class classification to build an efficient and robust prediction model using multilayer perceptron (MLP), logistic regression (LR), and random forest (RF) for bug severity classification. Both tests are performed on two software error datasets, namely Ant 1.7 and Tomcat.
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Conference papers on the topic "Consumers Classification Computer programs"

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"CONCEPT CLASSIFICATION FOR STUDY PROGRAMS QUALITY EVALUATION." In 2nd International Conference on Computer Supported Education. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0002775404410445.

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Chan, W. K., Jeffrey C. F. Ho, and T. H. Tse. "Piping Classification to Metamorphic Testing: An Empirical Study towards Better Effectiveness for the Identification of Failures in Mesh Simplification Programs." In 31st Annual International Computer Software and Applications Conference - Vol. 1- (COMPSAC 2007). IEEE, 2007. http://dx.doi.org/10.1109/compsac.2007.167.

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Rejman, Krystyna, Marzena Jeżewska-Zychowicz, and Grzegorz Ganczewski. "Understanding the Concept of Sustainable Food Consumption – whether it will Reduce Meat Consumption." In 14th International Scientific Conference "Rural Environment. Education. Personality. (REEP)". Latvia University of Life Sciences and Technologies. Faculty of Engineering. Institute of Education and Home Economics, 2021. http://dx.doi.org/10.22616/reep.2021.14.041.

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Despite the evidence-based health and environment benefits of sustainable diets and the urgent need to change consumption patterns in well-developed countries into plant-based diet, people are reluctant to limit meat consumption. The aim of the study was to examine the attachment to meat consumption in a group of Polish consumers and whether it depends on an understanding of the concept of sustainable food consumption (SFC). The study was carried out using the Computer Assisted Web Interview method on a sample of 199 consumers, who met two criteria of inclusion: age (20 - 65 years old) and not excluding meat from the diet. The questionnaire included a tool to measure the attachment to eating meat in 4 dimensions: hedonism, affinity, entitlement, and dependence. The analysis of the results was carried out in the Statistica software. Pearson Chi-squared test and Student’s t-test were performed to investigate the significance of differences between the two variables (p≤0.05). In the surveyed group only 35 % of respondents interpreted the term of sustainable food consumption correctly and among them there were more people with higher education. Interviewees were rather strongly attached to eating meat and this was firstly due to the belief in human right to eat meat, secondly – taste preferences and hedonism, thirdly ‒ dependence on eating meat. The ethical motives (affinity) were rated lowest, but significantly higher by respondents understanding the concept of sustainable diet. Their opinions on all aspects of attachment to eating meat were more pro-environmental than those of respondents who did not understand the idea (although the differences in the opinions were not statistically significant). Our results indicate the need to implement effective educational programs that will show all benefits of a sustainable diet to provide consumers with reliable knowledge and on this basis influence their attitudes and support them in making healthier and more sustainable choices in the food market.
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Pyo, Changmin, Sungwoo Park, Namhoon Kim, Junghoon Kwon, and Kunwoo Lee. "Computer-Aided Analysis of Muscular Movement of Lower Limbs and Gait Change When Walking With Unstable Shoes." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-69033.

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Several healthcare products have been developed and marketed in recent times as a result of people’s growing interest in personal health. Unstable shoes have been introduced to revitalize the muscles of the lower limbs and to modify the gait posture while walking. However, healthcare products for people should first be proved functional and safe, as some of those can sometimes result in severe injuries and side effects. Certification is, therefore, necessary in the case of unstable shoes. In this study, the functionality of unstable shoes was analyzed; it was proved that difference in pressure distribution resulting from the shape of the unstable shoes helps strengthen the muscles of the lower limbs. These analyses focused on the activation of the muscles by employing EMG (Electromyography). However, the approach involving EMG cannot carry out measurements on hidden muscles, and the noise involved is a source of potential error; therefore, this study utilizes the simulation software SIMM (Software for Interactive Musculoskeletal Modeling) for this purpose. We performed a biomechanical study using a full-body musculoskeletal model. Using the captured 3D motion data and ground reaction forces data, kinetic data was calculated in order to determine its influence on the adjacent segments. We captured the movements of six volunteers, all males in their twenties. The volunteers wore both unstable and normal shoes during each trial. This study focuses on the activation of muscles of the lower limbs when wearing unstable shoes. We inspected the muscles and analyzed the disparities between unstable and normal shoes. We observed from experimental results that most muscles of the lower limbs were revitalized. Further, we observed an improvement in the gait posture after unstable shoes were used for a period of 12 weeks. This analysis of inner muscles that cannot be examined by direct methods can help consumers make informed choices regarding healthcare products. Such analysis is made possible by simulation programs such as SIMM.
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Hentea, Mariana. "A Perspective on Achieving Information Security Awareness." In InSITE 2005: Informing Science + IT Education Conference. Informing Science Institute, 2005. http://dx.doi.org/10.28945/2855.

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The guidelines “Towards a Culture of Security” emphasize a culture of security in all aspects of information systems, from designing and planning through to everyday use, and among all participants, from government down through business to consumers. In response to national needs, Information Security education has become a priority for many educational institutions in US for the past years. More universities and colleges have established courses or specialized programs to teach Information Security skills to students enrolled in degrees related to computers such as computer information systems, computer engineering, and computer science. However, there are aspects of the security education model that need attention. This paper discusses these issues including changes to improve security awareness education. Through close coordination between faculty, industry, government agencies, and universities, the critical education of future graduates, Information Technology professionals, Information Security professionals, and public can be accelerated.
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Adeoye, A. O. M., and T. Sze´csi. "The Use of Hybrid System of Classification for the Retrieval and Modification of Mechanical Products." In ASME 2011 International Manufacturing Science and Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/msec2011-50157.

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With people becoming more individualistic in their choices they make in personalizing the goods and services they use, as resulted in major development that has been recorded in the customisation world. This individualism has resulted in the increase in demand of customized products in many industries especially in the footwear, kitchen and computer industries. However, little has been done when it comes to mechanically oriented products and little flexibility has been given to the consumers in the co-creation of customized products. The Hybrid system of classification is one way to satisfy the customers’ need for the products that are mechanically oriented in nature thereby meeting their desire needs. This paper presents a framework in which an Hybrid system of classification is used to integrates Customers into the design process by defining, configuring, matching, or modifying personal product that is mechanically oriented in nature and grouping the products into classes and sub-classes using a wide range of product parameters, products configuration which make it possible to add and/or change functionalities of a core product, a coding system for mechanical designs which is applicable to each product in the hierarchy, the use of a database for the products information. And the retrieval system to retrieve a similar product code from the database if the initial customer configuration data does not yield a feasible product code through the application of Analytic Hierarchy Process and finally modifying the existing similar product to suit the customers desire.
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Chen, Yifan, Basavaraj Tonshal, Pramita Mitra, Craig Simonds, and Paul Aldighieri. "A Novel Approach to the Design and Development of an Interactive Learning App for Automotive IVI Systems." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47906.

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Since its launch Ford SYNC™ with MyFord Touch™ in-vehicle infotainment (IVI) system has migrated to many vehicle programs and had multiple software updates, which presented Ford dealers with the ever-increasing challenge of training new owners effectively and efficiently. This paper presents the design, architecture and implementation of “MyFord Touch Guide”, a novel, cross-platform mobile app that delivers a unique MyFord Touch learning and familiarization experience for dealers and consumers alike. This app incorporates the production MyFord Touch graphical user interface for an interactive learning experience. Additionally, it integrates a host of video tutorials featuring a computer-animated character, which offers an insightful, personalized and self-guided tour experience of the essential features and functions of the system. MyFord Touch Guide is a cross-platform app and based on a “hybrid” app architecture that uses both native mobile and web technologies. Feedback gathered from multiple nation-wide surveys indicates that the proposed approach provides a highly effective and scalable solution towards developing a diverse range of cross-platform, interactive, mobile learning apps.
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Lucca Junior, Horacio Emidio de, and Arnaldo Rodrigues Santos Jr. "Classification of Mammographic Images by Openvino: A Proposal of use to Enhance More Effectivity in Cancer Diagnosis." In 2nd International Conference on Machine Learning, IOT and Blockchain (MLIOB 2021). Academy and Industry Research Collaboration Center (AIRCC), 2021. http://dx.doi.org/10.5121/csit.2021.111206.

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Diseases that are characterized by the disordered growth of cells that, in many cases, have the property of invading tissues and organs are commonly called cancer. Such cells divide quickly and the invasion can be very aggressive and uncontrolled, resulting in formation of malignant tumors Mammographic images from libraries of the American digital database DDSM were used in this research for digital improvement and characteristic analysis using the OpenVino computer program This work has as main objective to analyze mammography images of breast nodules and to propose a method of classification by shape and texture using computer programs that can maximize the accuracy in the correct diagnosis regarding the malignancy or not of a tumor. It is a tool that it can be useful as a contribution in the interpretation of the results to mastologists who identify such nodules through the analyzed radiological images.
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Ferguson, Eric, Toby Dunne, Lloyd Windrim, Suchet Bargoti, Nasir Ahsan, and Waleed Altamimi. "Automated Painting Survey, Degree of Rusting Classification, and Mapping with Machine Learning." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/208119-ms.

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Abstract Objective Continuous fabric maintenance (FM) is crucial for uninterrupted operations on offshore oil and gas platforms. A primary FM goal is managing the onset of coating degradation across the surfaces of offshore platforms. Physical field inspection programs are required to target timely detection and grading of coating conditions. These processes are costly, time-consuming, labour-intensive, and must be conducted on-site. Moreover, the inspection findings are subjective and provide incomplete asset coverage, leading to increased risk of unplanned shutdowns. Risk reduction and increased FM efficiency is achieved using machine learning and computer vision algorithms to analyze full-facility imagery for coating degradation and subsequent ‘degree-of-rusting’ classification of equipment to industry inspection standards. Methods, Procedures, Process Inspection data is collected for the entirety of an offshore facility using a terrestrial scanner. Coating degradation is detected across the facility using machine learning and computer vision algorithms. Additionally, the inspection data is tagged with unique piping line numbers per design, fixed equipment tags, or unique asset identification numbers. Computer vision algorithms and the detected coating degradation are subsequently used as input to determine the ‘degree-of-rusting’ throughout the facility, and coating condition status is tagged to specific piping or equipment. The degree-of-rusting condition rating follows common industry standards used by inspection engineers (e.g., ISO 4628-3, ASTM D610-01, or European Rust Scale). Results, Observations, Conclusions Atmospheric corrosion is the number one asset integrity threat to offshore platforms. Utilizing this automatic coating condition technology, a comprehensive and objective analysis of a facility's health is provided. Coating condition results are overlaid on inspection imagery for rapid visualisation. Coating condition is associated with individual instances of equipment. This allows for rapid filtering of equipment by coating condition severity, process type, equipment type, etc. Fabric maintenance efficiencies are realized by targeting decks, blocks, or areas with the highest aggregate coating degradation (on process equipment or structurally, as selected by the user) and concentrating remediation efforts on at-risk equipment. With the automated classification of degree-of-rusting, mitigation strategies that extend the life of the asset can be optimised, resulting in efficiency gains and cost savings for the facility. Conventional manual inspections and reporting of coating conditions has low objectivity and increased risk and cost when compared to the proposed method. Novel/Additive Information Drawing on machine learning and computer vision techniques, this work proposes a novel workflow for automatically identifying the degree-of-rusting on assets using industry inspection standards. This contributes directly to greater risk awareness, targeted remediation strategies, improving the overall efficiency of the asset management process, and reducing the down-time of offshore facilities.
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Renner, Alex, Joseph Holub, Shubang Sridhar, Gabe Evans, and Eliot Winer. "A Virtual Reality Application for Additive Manufacturing Process Training." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47807.

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The promise of cheap and widely available 3D printers may be one of the best and worst aspects of Additive Manufacturing (AM). A non-technical consumer may pay significantly more for a 3D printer with “no assembly required”. Since it is reasonable to assume that they may not understand how the printer works and what will come out of it, they may wind up returning it because it does not meet their expectations. While consumers are starting to use 3D printers, designers in industry are utilizing Rapid Prototyping (RP) machines to manufacture final products in addition to prototypes. Designers will need to know AM principles in order to communicate design specifications to a RP lab technician so that a part passes Quality Assurance inspection. Training users on fundamental layer-based manufacturing methods can assist before and after a 3D printer purchase and reduce the strain on RP labs in industry. This paper presents an extensible software application that simulates an AM process in a Virtual Reality (VR) environment. The application parses machine component movements and printed segment attributes from G-code files exported from the MakerBot® Computer Aided Manufacturing (CAM) software. Position, speed, and type of movement are used to simulate the physical machine movements. A print “segment” is created at the start and end positions of a print movement. Color-coding segment attributes and modifying their size and shape establishes a visual relationship between terminology for a print setting and its representation in the virtual environment. This visual relationship between printed segments and print settings makes it easier to learn the 3D printing process and associated terminology. Novice and expert users can modify print settings in the virtual environment before and after printing a prototype. Identifying and fixing a mistake in the virtual environment reduces the time and cost to print a part with the desired quality. Training multidisciplinary users in a virtual world allows them to explore AM processes in detail from any angle or scale desired. This application has been tested in a cube shaped virtual reality CAVE system with each side measuring ten feet powered by a 96-node graphics computer cluster. Approximately 20 hours of demonstrations have been performed for public outreach programs related to STEM initiatives and visitors from industry who have had a variety of AM experience.
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