Relevant bibliographies by topics / Auto-generate

Contents

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

Academic literature on the topic 'Auto-generate'

Author: Grafiati
Published: 4 June 2021
Last updated: 18 February 2022

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Journal articles on the topic "Auto-generate"

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Ariestanti, Hani Dewi, Ignatius Joko Dewanto, DwiSloria Suharti, and Muhamad Yusup. "Implementation of Lecture Scheduling Using Method – Auto Generate Timetable." International Journal of Engineering and Technology 10, no. 6 (2018): 1669–80. http://dx.doi.org/10.21817/ijet/2018/v10i6/181006038.

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Qin, Hao, Shao Xiong Long, and Kai Yu. "Simulation Research on the Shift Schedule in the Auto with Automated Manual Transmission Based on Cruise Gear Shift Program." Advanced Materials Research 712-715 (June 2013): 2160–63. http://dx.doi.org/10.4028/www.scientific.net/amr.712-715.2160.

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Shift schedule has an important influence on the performances of the auto with automated manual transmission (AMT). It will affect fuel economy, dynamic and emission performance of vehicle. According to the numbers of the control parameters, shift schedule can be roughly divided into threemain categories: single parameter, two parameters, and three parameters schedule.This paper introduces how to simulate and generate the shift schedule in the auto with AMT on the basis of two parameters shift schedule which is widely used in the real auto engineering by using the Gear Shift Program (GSP) module of the Cruise software.The result shows that this method could generate the shift schedule accurately and quickly.These works could be used in the effective calibration of transmissions and shorten thevehicle development cycle.
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Sa’adah, Lailis, Frida Agung Rakhmadi, and Rini Widyaningrum. "Fluorescence Imaging System Using High Power LED to Generate Oral Auto-fluoerscence of Sprague dawley Rat." Proceeding International Conference on Science and Engineering 1 (October 31, 2017): 183–87. http://dx.doi.org/10.14421/icse.v1.298.

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It is difficult to distinguish oral cancer and normal oral mucosa in clinical examination. Hence, it is important to develop a diagnostic tool to aid clinical practitioners to examine and diagnose abnormalities in oral cavity. One of methods applied for this purpose was based on tissue auto-fluorescence. The purpose of this study was to develop a fluorescence imaging (FI) system using High Power LED (HPL) as excitation source. There were 3 HPL with different wavelengths used in this study, i.e. 385, 420, and 455 nm. The system was aimed to generate as well as to detect the auto-fluorescence effect of oral cavity in Sprague dawley rats. This study was done in 6 steps, i.e. development of FI system, early test of FI system using coconut oil, palm oil, olive oil, eucalyptus oil, and pure water as samples, followed by finishing of the system, image acquisition of oral cavity auto-fluorescence from 3 samples of Sprague dawley rats, and the last step was data analysis to determine the best wavelength of HPL for FI system developed in this study. Auto-fluorescence images were obtained by exposing samples by using HPL, then auto-fluorescence effect emitted by samples were captured using Canon EOS D600 camera. Auto-fluorescence intensity from images were analyzed using MATLAB R2008a. Results of this study showed that the best HPL wavelength used for the FI system was 385 nm that was captured with filter in the camera. The auto-fluorscence image produced by using HPL 385nm was showed the lowest intensities.
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Kosikova, Tamara, and Douglas Philp. "Exploring the emergence of complexity using synthetic replicators." Chemical Society Reviews 46, no. 23 (2017): 7274–305. http://dx.doi.org/10.1039/c7cs00123a.

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Mustafa, Asma. "Faith and Photography." Fieldwork in Religion 9, no. 2 (2015): 166–81. http://dx.doi.org/10.1558/firn.v9i2.14821.

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This article explores the usage of the innovative method of auto photography in eliciting perceptions of religious identity. The article explores auto-photography as a research tool assisting in understanding religious identity and identification. Using static images in auto-photography triggers the respondents in expressing their connection to their faith. These images have a potential to generate further discussion on the subject matter of faith, religiousness and belief. Auto-photography is a helpful instrument in bridging spiritual feelings/thoughts and religiously oriented actions. It encourages respondents to express their feelings regarding faith after exploring the images taken using a camera. This article debates the use of auto photography through the case study of young Muslims in Britain. Based on this research project, the auto-photography method will be analysed as a research tool, revealing its usefulness in exploring faith matters and the challenges of using this method.
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Lu, Xiao Bo, La Zhu Hao, and Li Fang Yan. "Test Paper Materials Auto-Generation System." Applied Mechanics and Materials 484-485 (January 2014): 808–11. http://dx.doi.org/10.4028/www.scientific.net/amm.484-485.808.

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Nowadays, the computer is increasingly popular, and college examination is developing in the direction of traditional examination means to automation and intelligence ones gradually, all these make it inevitable to construct question bank for courses, and to generate test paper using computers. This paper uses the Delphi technique, to make improvements to existing components, combining with VBA programming, and use of SQL Server to implement the question bank management and test paper auto-generation system, which could generate test paper in Word Document. A large number of tests show that the software is running stably and system features are functioning correctly on Windows 2000/XP/2003 platform with Office XP/2003 environment.
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Okamura, H., T. Dohi, and S. Osaki. "A structural approximation method to generate the optimal auto-sleep schedule for computer systems." Computers & Mathematics with Applications 46, no. 7 (2003): 1103–10. http://dx.doi.org/10.1016/s0898-1221(03)90125-8.

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Bellani, Giacomo, Andrea Coppadoro, Nicolò Patroniti, et al. "Clinical Assessment of Auto-positive End-expiratory Pressure by Diaphragmatic Electrical Activity during Pressure Support and Neurally Adjusted Ventilatory Assist." Anesthesiology 121, no. 3 (2014): 563–71. http://dx.doi.org/10.1097/aln.0000000000000371.

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Abstract Background: Auto-positive end-expiratory pressure (auto-PEEP) may substantially increase the inspiratory effort during assisted mechanical ventilation. Purpose of this study was to assess whether the electrical activity of the diaphragm (EAdi) signal can be reliably used to estimate auto-PEEP in patients undergoing pressure support ventilation and neurally adjusted ventilatory assist (NAVA) and whether NAVA was beneficial in comparison with pressure support ventilation in patients affected by auto-PEEP. Methods: In 10 patients with a clinical suspicion of auto-PEEP, the authors simultaneously recorded EAdi, airway, esophageal pressure, and flow during pressure support and NAVA, whereas external PEEP was increased from 2 to 14 cm H2O. Tracings were analyzed to measure apparent “dynamic” auto-PEEP (decrease in esophageal pressure to generate inspiratory flow), auto-EAdi (EAdi value at the onset of inspiratory flow), and IDEAdi (inspiratory delay between the onset of EAdi and the inspiratory flow). Results: The pressure necessary to overcome auto-PEEP, auto-EAdi, and IDEAdi was significantly lower in NAVA as compared with pressure support ventilation, decreased with increase in external PEEP, although the effect of external PEEP was less pronounced in NAVA. Both auto-EAdi and IDEAdi were tightly correlated with auto-PEEP (r2 = 0.94 and r2 = 0.75, respectively). In the presence of auto-PEEP at lower external PEEP levels, NAVA was characterized by a characteristic shape of the airway pressure. Conclusions: In patients with auto-PEEP, NAVA, compared with pressure support ventilation, led to a decrease in the pressure necessary to overcome auto-PEEP, which could be reliably monitored by the electrical activity of the diaphragm before inspiratory flow onset (auto-EAdi).
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Jiang, Shao Fei, Chun Fu Lu, and Cong Da Lu. "Template-Based Process Planning System for Special Bearing." Key Engineering Materials 407-408 (February 2009): 243–47. http://dx.doi.org/10.4028/www.scientific.net/kem.407-408.243.

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This paper reports the work of web-based auto-design machining process of special bearing. A template-based process planning method is proposed for auto generating machining process of special bearing, including turning process and grinding process of inner ring or outer ring. Process templates are customized to generate process, procedures size and size tolerance are calculated according to procedure size database. A web-based process planning system is developed based on the proposed method. The use of the system is illustrated with an example.
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Krumin, Michael, and Shy Shoham. "Generation of Spike Trains with Controlled Auto- and Cross-Correlation Functions." Neural Computation 21, no. 6 (2009): 1642–64. http://dx.doi.org/10.1162/neco.2009.08-08-847.

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Emerging evidence indicates that information processing, as well as learning and memory processes, in both the network and single-neuron levels are highly dependent on the correlation structure of multiple spike trains. Contemporary experimental as well as theoretical studies that involve quasi-realistic neuronal stimulation thus require a method for controlling spike train correlations. This letter introduces a general new strategy for generating multiple spike trains with exactly controlled mean firing rates and correlation structure (defined in terms of auto- and cross-correlation functions). Our approach nonlinearly transforms random gaussian-distributed processes with a predistorted correlation structure into nonnegative rate processes, which are then used to generate doubly stochastic Poisson point processes with the required correlation structure. We show how this approach can be used to generate stationary or nonstationary spike trains from small or large groups of neurons with diverse auto- and cross-correlation structures. We analyze and derive analytical formulas for the high-order correlation structure of generated spike trains and discuss the limitations of this approach.
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Dissertations / Theses on the topic "Auto-generate"

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McPherson, Mercedes. "Auto-Generating Maps Using Open-Source GIS and Python." The University of Arizona, 2017. http://hdl.handle.net/10150/626250.

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Fund for the Arts is one of the oldest arts fund in the country. Since its formation in 1949, the organization has raised over 200 million for the community, which includes Kentucky and Southern Indiana. This Master’s project will focus on one of the organization’s programs entitled 5x5. The goal of 5x5 is to expose elementary school students to five art experiences before they finish the fifth grade. Several years’ worth of data has been compiled, including school names, performance names, performance type, number of students served, and total cost, among others. Using a combination of these parameters, maps will be auto-generated using CSV templates. The auto-generated maps will show a variety of data, including the amount of art funding per zip code, per program type, per grade, per art group, per school, and per student. The maps will serve as visual evidence of the program’s progress and will be shared with Fund for the Arts Board of Directors and CEO, internal staff, as well as other community stakeholders such as community liaisons, participating schools, current and potential donors and the Louisville Metro Council. Fund for the Arts is a nonprofit that does not have access to ESRI products. This Master’s project combines cartography and scripting to create a functioning deliverable using open-source GIS software that enables the organization to auto-generate maps at will and forego the need to request maps from the local university once a year.
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Falcone, Morena. "Caratterizzazione sperimentale delle strutture vorticose generate in coda ad un'auto solare." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15229/.

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Quest’attività di tesi portava con sé numerosi obbiettivi, primo tra tutti la conoscenza della galleria del vento. Questa è servita per tutta la fase sperimentale dell'acquisizione delle misure. L’iniziale fase di ricerca ha riguardato la classificazione delle gallerie del vento. Altre ricerche hanno interessato gli strumenti che più comunemente si utilizzano per le misure di velocità. Successivamente si è passati alla parte sperimentale vera a propria. Tramite l’uso di un tubo di Pitot, sono state eseguite diverse misure di velocità nella camera di prova della galleria del vento per frequenze da 5 Hz a 40 Hz. Questo lavoro ha portato alla caratterizzazione della galleria: con i risultati ottenuti è stato possibile tracciare grafici 2D e 3D dell’andamento delle velocità. Nella seconda parte sperimentale è stata usata la tecnologia PIV, per analizzare il flusso intorno a un cilindro con frequenze dai 5 Hz ai 20 Hz. Tramite il software FlowManager che gestiva il laser e i dispositivi fotografici è stato possibile acquisire fotogrammi del flusso che si scontrava contro l'ostacolo. Con un lavoro di post-processing si è arrivati ad ottenere mappe 3D dei campi di velocità. La terza ed ultima parte sperimentale ha riguardato nuove misure con la tecnica PIV, alle stesse frequenze considerate nella fase precedente, ma questa volta l'ostacolo impiegato è stato il modello in scala 1:18 dell'automobile solare Emilia4, sviluppata dal team Onda Solare. In particolare, si sono voluti indagare i fenomeni turbolenti che avvengono in coda all'auto.Le difficoltà in questo caso sono state maggiori a causa di fenomeni di mescolamento tra flussi, per vortici 3D di complicata analisi dalla tecnologia stereo-PIV e perché il flusso era notevolmente più turbolento. Il conclusivo calcolo dei numeri di Reynolds per entrambi i casi (flusso intorno al cilindro e in coda all'auto) ha permesso un confronto con i casi presenti in letteratura ed ha validato le sperimentazioni.
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LU, MEI-CHI, and 盧梅綺. "The Research on Repurchase Behavior for Auto Industry－The Business Intelligence to Generate Target Consumer List." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/49007063165013004587.

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碩士<br>國立臺北大學<br>企業管理學系<br>91<br>The research integrates theoretical and practical methods and investigates the repurchase behavior of customers in the auto industry. It consists of three purposes. First, we develop business intelligence logics to generate target consumer lists from the data. Second, according to the loyalty segmentation, we can generate the priority of target consumer lists. Last, we predict the choosing car type according to the using of per consumer. Through research methods such as studying the survey on repurchase behavior of customers and business intelligence, and having interviews with experts, sales and customers, we induce the research dimension of business intelligence logic. According to the dimension, we develop the business intelligence logic to generate target consumer list, set up hypotheses and design the questionnaire. We use Univariate T-test and Chi-square Test of Goodness of Fit to correct the business intelligence logic. Then, we use Regression to prove the relationship between loyalty and satisfaction and One-way ANOVA and Decision Tree to generate the loyalty segmentation. Finally, we use Discriminate Analysis to predict the choosing car type. After developing the conceptual framework and analyzing, we have three conclusions. First, we develop business intelligence logics to generate target consumer lists and use data to prove the feasibility of business intelligence logics. Second, according to the loyalty segmentation, we can generate the priority of target consumer lists. Last, we predict the choosing car type according to the using of per consumer. Summarily, we can provide sales of auto companies with target consumer lists, the priority of target consumer lists, and the prediction of the choosing car type.
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Books on the topic "Auto-generate"

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generate extra money auto-pilot. Easy money, 2020.

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Book chapters on the topic "Auto-generate"

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Cinar, Onur. "Auto-Generate JNI Code Using SWIG." In Pro Android C++ with the NDK. Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-4828-6_4.

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Fan, Penghui, Shuyan Wang, and Jiaze Sun. "An Auto-Adapted Method to Generate Pairwise Test Data Set." In Artificial Intelligence and Computational Intelligence. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33478-8_30.

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Yu, Hai, Zi-Xuan Li, and Yu-Yan Jiang. "Using GitHub Open Sources and Database Methods Designed to Auto-Generate Chinese Tang Dynasty Poetry." In Communications in Computer and Information Science. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7530-3_32.

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Prada-Ospina, Ricardo. "Corporate Entrepreneurship as a Tool for Organizational Improvement." In Handbook of Research on Intrapreneurship and Organizational Sustainability in SMEs. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3543-0.ch015.

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Auto parts companies are an integral part of the automobile sector, which constitutes an important economic item within the metalworking industry. Its goal is to carry out productive work by integrating the largest possible number of automotive parts and national added value pieces. Corporate entrepreneurship, studied at both the academic and business levels, tries to generate new business schemes or the creation of new companies from the efficient use of available resources and the recognition of opportunities for the improvement and innovation of companies. This chapter shows how corporate entrepreneurship should be a key tool in auto parts organizational improvement. In order to deepen the understanding of the relationship between corporate entrepreneurship and auto parts companies, the study is complemented by the results obtained in the report of the Global Entrepreneurship Monitor (GEM) of Colombia.
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Sudarshana, Kerenalli, and Mylarareddy C. "Recent Trends in Deepfake Detection." In Advances in Computational Intelligence and Robotics. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7728-8.ch001.

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Almost 59% of the world's population is on the internet, and in 2020, globally, there were more than 3.81 billion individual social network users. Eighty-six percent of the internet users were fooled to spread fake news. The advanced artificial intelligence (AI) algorithms can generate fake digital content that appears to be realistic. The generated content can deceive the users into believing it is real. These fabricated contents are termed deepfakes. The common category of deepfakes is video deepfakes. The deep learning techniques, such as auto-encoders and generative adversarial network (GAN), generate near realistic digital content. The content generated poses a serious threat to the multiple dimensions of human life and civil society. This chapter provides a comprehensive discussion on deepfake generation, detection techniques, deepfake generation tools, datasets, applications, and research trends.
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Rossdale, Chris. "Contestations." In Resisting Militarism. Edinburgh University Press, 2019. http://dx.doi.org/10.3366/edinburgh/9781474443036.003.0007.

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This chapter considers how anti-militarists challenge militarised forms of contestation by prefiguring alternatives. The chapter opens by introducing again the concept of prefiguration, which holds that the means used to achieve political change will shape or become the ends that result. It then considers three distinct anti-militarist practices – peace camps, die-ins, and the use of humour – showing how each of these is guided by a desire to generate subjectivities and relationalities which do not reproduce militarism. In contrast, the last part of the chapter considers how anti-militarism is shaped not simply by opposition to militarism, but also by desire for it. Drawing on auto-ethnographic reflections, the discussion outlines how acknowledging the role of desire in social movements deepens the radical promise of prefiguration.
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Levy, Richard. "Apathy." In Apathy. Oxford University Press, 2021. http://dx.doi.org/10.1093/med/9780198841807.003.0009.

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‘Auto-activation’ deficit, the most severe form of apathy, is a model to approach apathy. Auto-activation deficit consists of a severe reduction in self-initiated actions contrasting with the sparing of externally driven ones under strong solicitations and the presence of automatic (stereotypic) behaviour. This severe apathy can be viewed as the consequence of a quantitative reduction of goal-directed behaviour. Auto-activation deficit is due to lesions in the prefrontal cortex (PFC)–basal ganglia circuitry, the brain system that generates and controls goal-directed behaviour. In this chapter it is proposed that several different mechanisms may be responsible for apathy. Damage to three PFC–basal ganglia circuits may explain most of the cases of apathy: (i) lesions in the orbital and ventromedial PFC–basal ganglia circuit lead to apathy through difficulties in evaluating the affective value of a given behavioural context (‘amotivation’); (ii) lesions in the lateral PFC–basal ganglia circuit contribute to apathy via an inability to generate or activate strategies required to successfully complete a given programme of actions (‘cognitive inertia’); (iii) lesions to the anterior cingulate cortex–basal ganglia circuit (located in an intermediary anatomical position between the ventral and lateral circuit) may lead to apathy via an inability to transfer the affective value of a given context (‘invigoration deficit’); (iv) the summation or the synergy of damage to these three circuits within the basal ganglia may lead to a frank decrease in the amplification of signals representing goal-directed behaviour that reach the PFC (‘empty mind’); and (v) if all three circuits are structurally intact, apathy may nevertheless occur via alterations of neurotransmission systems that modulate the activity of these circuits (i.e. dopamine, serotonin, and acetylcholine).
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Zhang, Lei. "Evaluating the Effects of Size and Precision of Training Data on ANN Training Performance for the Prediction of Chaotic Time Series Patterns." In Research Anthology on Artificial Neural Network Applications. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-2408-7.ch012.

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In this research, artificial neural networks (ANN) with various architectures are trained to generate the chaotic time series patterns of the Lorenz attractor. The ANN training performance is evaluated based on the size and precision of the training data. The nonlinear Auto-Regressive (NAR) model is trained in open loop mode first. The trained model is then used with closed loop feedback to predict the chaotic time series outputs. The research goal is to use the designed NAR ANN model for the simulation and analysis of Electroencephalogram (EEG) signals in order to study brain activities. A simple ANN topology with a single hidden layer of 3 to 16 neurons and 1 to 4 input delays is used. The training performance is measured by averaged mean square error. It is found that the training performance cannot be improved by solely increasing the training data size. However, the training performance can be improved by increasing the precision of the training data. This provides useful knowledge towards reducing the number of EEG data samples and corresponding acquisition time for prediction.
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Quah, Jon T. S., Winnie C. H. Leow, and K. L. Yong. "Auto-Personalization Web Pages." In Human Computer Interaction. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-87828-991-9.ch052.

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This project experiments with the designing of a Web site that has the self-adaptive feature of generating and adapting the site contents dynamically to match visitors’ tastes based on their activities on the site. No explicit inputs are required from visitors. Instead a visitor’s clickstream on the site will be implicitly monitored, logged, and analyzed. Based on the information gathered, the Web site would then generate Web contents that contain items that have certain relatedness to items that were previously browsed by the visitor. The relatedness rules will have multidimensional aspects in order to produce cross-mapping between items. The Internet has become a place where a vast amount of information can be deposited and also retrieved by hundreds of millions of people scattered around the globe. With such an ability to reach out to this large pool of people, we have seen the expulsion of companies plunging into conducting business over the Internet (e-commerce). This has made the competition for consumers’ dollars fiercely stiff. It is now insufficient to just place information of products onto the Internet and expect customers to browse through the Web pages. Instead, e-commerce Web site designing is undergoing a significant revolution. It has become an important strategy to design Web sites that are able to generate contents that are matched to the customer’s taste or preference. In fact a survey done in 1998 (GVU, 1998) shows that around 23% of online shoppers actually reported a dissatisfying experience with Web sites that are confusing or disorganized. Personalization features on the Web would likely reverse this dissatisfaction and increase the likelihood of attracting and retaining visitors. bring the following benefits: 1. Attract and maintain visitors with adaptive contents that are tailored to their taste. 2. Target Web contents correspondingly to their respective audience, thus reducing information that is of no interest to the audience. 3. Advertise and promote products through marketing campaigns targeting the correct audience. 4. Enable the site to intelligently direct information to a selective or respective audience.
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Jardetzky, T. "The Interaction of Antigens and Superantigens with the Human Class II Major Histocompatibility Complex Molecule HLA-DR1." In Biological NMR Spectroscopy. Oxford University Press, 1997. http://dx.doi.org/10.1093/oso/9780195094688.003.0022.

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The initiation and maintenance of an immune response to pathogens requires the interactions of cells and proteins that together are able to distinguish appropriate non-self targets from the myriadof self-proteins (Janeway and Bottomly, 1994). This discrimination between self and non-self is in part accomplished by three groups of proteins of the immune system that have direct and specific interactions with antigens: antibodies, T cell receptors (TcR) and major histocompatibility complex (MHC) proteins. Antibodies and TcR molecules are clonally expressed by the B and T cells of the immune system, respectively, defining each progenitor cell with a unique specificity for antigen. In these cell types both antibodies and TcR proteins undergo similar recombination events to generate a variable antigen combining site and thus produce a nearly unlimited number of proteins of different specificities. TcR molecules are further selected to recognize antigenic peptides bound to MHC proteins, during a process known as thymic selection, restricting the repertoire of T cells to the recognition of antigens presented by cells that express MHC proteins at their surface. Thymic selection of TcR and the subsequent restricted recognition of peptide-MHC complexes by peripheral T cells provides a fundamental molecular basis for the discrimination of self from non-sell and the regulation of the immune response (Allen, 1994; Nossal, 1994; von Boehmer, 1994). For example, different classes of T cells are used to recognize and kill infected cells (cytotoxic T cells) arid to provide lymphokiries that induce the niajority of soluble antibody responses of B cells (helper T cells). In contrast to the vast combinatorial and clonal diversity of antibodies and TcRs, a small set of MHC molecules is used to recognize a potentially unlimited universe of foreign peptide antigens for antigen presentation to T cells (Germain, 1994). This poses the problem of how each MHC molecule is capable of recognizing enough peptides to insure an immune response to pathogens. In addition, the specificity of the TcR interaction with MHC-peptide complexes is clearly crucial to the problem of self :non-self discrimination, with implications for both protective immunity and auto-immune disease.
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Conference papers on the topic "Auto-generate"

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Ilham, Nur Iqtiyani, E. H. Mat Saat, N. H. Abdul Rahman, Farah Yasmin Abdul Rahman, and Nurhani Kasuan. "Auto-generate scheduling system based on expert system." In 2017 7th IEEE International Conference on Control System, Computing and Engineering (ICCSCE). IEEE, 2017. http://dx.doi.org/10.1109/iccsce.2017.8284370.

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Giese, Martin, Jens Ingvald Ornas, Lars Overå, Inge Svensson, and Arild Waaler. "Using Semantic Technology to Auto-generate Reports: Case Study of Daily Drilling Reports." In SPE Intelligent Energy International. Society of Petroleum Engineers, 2012. http://dx.doi.org/10.2118/150225-ms.

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Yin, Di, Jiwei Tan, Zhe Zhang, Hongbo Deng, Shujian Huang, and Jiajun Chen. "Learning to Generate Personalized Query Auto-Completions via a Multi-View Multi-Task Attentive Approach." In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. ACM, 2020. http://dx.doi.org/10.1145/3394486.3403350.

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Gunatilaka, C. C., A. J. Bates, E. B. Hysinger, et al. "Neonates with Tracheomalacia Generate Auto-PEEP via Glottis Closure Measured by MRI-Based Computational Fluid Dynamics." In American Thoracic Society 2021 International Conference, May 14-19, 2021 - San Diego, CA. American Thoracic Society, 2021. http://dx.doi.org/10.1164/ajrccm-conference.2021.203.1_meetingabstracts.a3312.

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Choi, Youngwon, and Joong-Ho Won. "Ornstein Auto-Encoders." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/301.

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We propose the Ornstein auto-encoder (OAE), a representation learning model for correlated data. In many interesting applications, data have nested structures. Examples include the VGGFace and MNIST datasets. We view such data consist of i.i.d. copies of a stationary random process, and seek a latent space representation of the observed sequences. This viewpoint necessitates a distance measure between two random processes. We propose to use Orstein's d-bar distance, a process extension of Wasserstein's distance. We first show that the theorem by Bousquet et al. (2017) for Wasserstein auto-encoders extends to stationary random processes. This result, however, requires both encoder and decoder to map an entire sequence to another. We then show that, when exchangeability within a process, valid for VGGFace and MNIST, is assumed, these maps reduce to univariate ones, resulting in a much simpler, tractable optimization problem. Our experiments show that OAEs successfully separate individual sequences in the latent space, and can generate new variations of unknown, as well as known, identity. The latter has not been possible with other existing methods.
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Li, Juncen, Ping Luo, Ganbin Zhou, Fen Lin, and Cheng Niu. "Adaboost with Auto-Evaluation for Conversational Models." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/580.

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We propose a boosting method for conversational models to encourage them to generate more human-like dialogs. In our method, we consider existing conversational models as weak generators and apply Adaboost to update those models. However, conventional Adaboost cannot be directly applied on conversational models. Because for conversational models, conventional Adaboost cannot adaptively adjust the weight on the instance for subsequent learning, result from the simple comparison between the true output y (to an input x) and its corresponding predicted output y' cannot directly evaluate the learning performance on x. To address this issue, we develop the Adaboost with Auto-Evaluation (called AwE). In AwE, an auto-evaluator is proposed to evaluate the predicted results, which makes it applicable to conversational models. Furthermore, we present the theoretical analysis that the training error drops exponentially fast only if certain assumption over the proposed auto-evaluator holds. Finally, we empirically show that AwE visibly boosts the performance of existing single conversational models and also outperforms the other ensemble methods for conversational models.
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Boutin, L., A. Eon, S. Zeghloul, and P. Lacouture. "An auto-adaptable algorithm to generate human-like locomotion for different humanoid robots based on motion capture data." In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010). IEEE, 2010. http://dx.doi.org/10.1109/iros.2010.5652230.

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Thébeau, Michèle A. "A Station Engineering Electrical/Controls Construction Database." In ASME 1995 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/95-gt-085.

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This paper will discuss the structure, features and capabilities of the Union Gas Ltd. Station Engineering Electrical/Controls Construction Database. The central feature of the application is the R:BASE database. In general, the database contains information which pertains to a transmission, measurement, regulating and/or compressor station. From the menu-driven custom application software used with R:BASE, the user can perform mass data manipulation to maintain the database, as well as create reports such as the equipment catalogue report. Finally, data can be extracted from the database to auto-generate junction box termination schedules as well as auto-generate, through a CAD software package, instrumentation loop drawings. These have the ability to show information such as panel and I/O module terminations, junction/termination box schedules, cable and conduit schedules, and device information such as alarm, shutdown and control setpoints.
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Desplats, Romain, Alban Eral, Felix Beaudoin, et al. "IC Diagnostic with Time Resolved Photon Emission and CAD Auto-Channeling." In ISTFA 2003. ASM International, 2003. http://dx.doi.org/10.31399/asm.cp.istfa2003p0045.

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Abstract The use of time resolved photon emission (TRPE) to compare internal measurements with simulations can dramatically reduce the time required for IC analysis. During debug, this technique makes it possible to probe only transistors of interest. Two limitations must be overcome: precise location of transistor photon emission areas and distinction between photons emitted by closely spaced transistors. Otherwise results may be seriously biased. Introducing CAD auto-channeling for TRPE makes it possible to generate virtual layers where emissions are expected. As a result, transistor TRPE areas can be automatically located and emission from nearby transistors is taken into account, thus significantly reducing the duration of IC analysis.
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Wang, Jing, Yingwei Pan, Ting Yao, Jinhui Tang, and Tao Mei. "Convolutional Auto-encoding of Sentence Topics for Image Paragraph Generation." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/132.

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Image paragraph generation is the task of producing a coherent story (usually a paragraph) that describes the visual content of an image. The problem nevertheless is not trivial especially when there are multiple descriptive and diverse gists to be considered for paragraph generation, which often happens in real images. A valid question is how to encapsulate such gists/topics that are worthy of mention from an image, and then describe the image from one topic to another but holistically with a coherent structure. In this paper, we present a new design --- Convolutional Auto-Encoding (CAE) that purely employs convolutional and deconvolutional auto-encoding framework for topic modeling on the region-level features of an image. Furthermore, we propose an architecture, namely CAE plus Long Short-Term Memory (dubbed as CAE-LSTM), that novelly integrates the learnt topics in support of paragraph generation. Technically, CAE-LSTM capitalizes on a two-level LSTM-based paragraph generation framework with attention mechanism. The paragraph-level LSTM captures the inter-sentence dependency in a paragraph, while sentence-level LSTM is to generate one sentence which is conditioned on each learnt topic. Extensive experiments are conducted on Stanford image paragraph dataset, and superior results are reported when comparing to state-of-the-art approaches. More remarkably, CAE-LSTM increases CIDEr performance from 20.93% to 25.15%.
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