Relevant bibliographies by topics / Driving database

Contents

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

Academic literature on the topic 'Driving database'

Author: Grafiati
Published: 28 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Driving database"

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Kasprzyk, A. "BioMart: driving a paradigm change in biological data management." Database 2011 (November 13, 2011): bar049. http://dx.doi.org/10.1093/database/bar049.

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Kossmann, Jan, and Rainer Schlosser. "Self-driving database systems: a conceptual approach." Distributed and Parallel Databases 38, no. 4 (March 16, 2020): 795–817. http://dx.doi.org/10.1007/s10619-020-07288-w.

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Abstract Challenges for self-driving database systems, which tune their physical design and configuration autonomously, are manifold: Such systems have to anticipate future workloads, find robust configurations efficiently, and incorporate knowledge gained by previous actions into later decisions. We present a component-based framework for self-driving database systems that enables database integration and development of self-managing functionality with low overhead by relying on separation of concerns. By keeping the components of the framework reusable and exchangeable, experiments are simplified, which promotes further research in that area. Moreover, to optimize multiple mutually dependent features, e.g., index selection and compression configurations, we propose a linear programming (LP) based algorithm to derive an efficient tuning order automatically. Afterwards, we demonstrate the applicability and scalability of our approach with reproducible examples.
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Lockemann, Peter C., Alfons Kemper, and Guido Moerkotte. "Future database technology: driving forces and directions." Future Generation Computer Systems 7, no. 1 (October 1991): 41–54. http://dx.doi.org/10.1016/0167-739x(91)90015-p.

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NAGIRI, Sueharu, Yasushi AMANO, and Syun'ichi DOI. "Performance Analysis and Database of Driving Maneuvers by using a Driving Simulator." Transactions of the Japan Society of Mechanical Engineers Series C 64, no. 627 (1998): 4338–44. http://dx.doi.org/10.1299/kikaic.64.4338.

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YAMAGISHI, Misako, Makoto INAGAMI, Takahiro TANAKA, Takashi YONEKAWA, Naoko KAWANO, Toshihisa SATO, Motoyuki AKAMATSU, and Hirofumi AOKI. "Driving Characteristics Database for Driving Assessment of Older Drivers: Data Repository for Human Life Driving Anatomy (Dahlia)." Japanese Journal of Ergonomics 56, no. 1 (February 15, 2020): 1–10. http://dx.doi.org/10.5100/jje.56.1.

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FUJINO, Naoki, Motoki SHINO, Machiko HIRAMATSU, Hideaki INOUE, Ryota SHIRATO, and Minoru KAMATA. "3207 Analysis on the deviant state while driving based on the driving behavior database." Proceedings of the Transportation and Logistics Conference 2009.18 (2009): 295–98. http://dx.doi.org/10.1299/jsmetld.2009.18.295.

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Mustafa, Rashed, Md Javed Hossain, and Thomas Chowdhury. "A better way for finding the optimal number of nodes in a distributed database management system." Daffodil International University Journal of Science and Technology 4, no. 2 (February 10, 2010): 19–22. http://dx.doi.org/10.3329/diujst.v4i2.4362.

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Distributed Database Management System (DDBMS) is one of the prime concerns in distributed computing. The driving force of development of DDBMS is the demand of the applications that need to query very large databases (order of terabytes). Traditional Client- Server database systems are too slower to handle such applications. This paper presents a better way to find the optimal number of nodes in a distributed database management systems. Keywords: DDBMS, Data Fragmentation, Linear Search, RMI. DOI: 10.3329/diujst.v4i2.4362 Daffodil International University Journal of Science and Technology Vol.4(2) 2009 pp.19-22
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Smith, David L., Wassim G. Najm, and Richard A. Glassco. "Feasibility of Driver Judgment as Basis for a Crash Avoidance Database." Transportation Research Record: Journal of the Transportation Research Board 1784, no. 1 (January 2002): 9–16. http://dx.doi.org/10.3141/1784-02.

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A crash avoidance database structure that is based on driver judgments is proposed. The structure comprises four driving conflict states (low risk, conflict, near crash, and crash) that correspond with advisory warning, crash-imminent warning, and crash mitigation counter-measures. The feasibility of this database structure is investigated by answering two questions: ( a) Can the driving states be reliably quantified? and ( b) Can the quantified states be used to create a useful crash avoidance database? The feasibility discussion centers on a specific dynamic scenario that involved braking maneuvers by a following vehicle to avoid a rear-end crash with a stopped lead vehicle. The quantification of driver judgment data from a controlled test track study is discussed as a foundation to identify rough quantitative locations for the conflict and near-crash state transitions, and crash data from a driving simulator experiment are used to estimate the crash state boundary. A database of on-road, naturalistic driving data is compared with the controlled experiments to evaluate the results. The method is found to be feasible, and recommendations for further development are presented.
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Alawneh, Ahmed Shlash, Osama Nusier, Abdullah I. Husein Malkawi, and Mustafa Al-Kateeb. "Axial compressive capacity of driven piles in sand: a method including post-driving residual stresses." Canadian Geotechnical Journal 38, no. 2 (April 1, 2001): 364–77. http://dx.doi.org/10.1139/t00-104.

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In this paper, empirical formulae were developed between the well-known pile bearing capacity factors (Nq and β) and parameters which include friction angle of sand, relative density, average effective vertical stress, and deformability of the soil below the pile toe. The developed empirical formulae were totally based on a database comprised of 28 well-documented compressive pile load tests collected exclusively from geotechnical literature. The actual measurements of shaft and end-bearing resistances of each pile in the database were adjusted to account for post-driving residual loads. Calculation of pile bearing capacity factors (Nq and β) was based on the adjusted shaft and end-bearing resistances rather than the actual unadjusted measured resistances for residual loads. Comparison of predicted and measured compressive capacity of an independent database comprised of 18 pile load tests showed that the developed formulae yield a reasonably accurate estimate of compressive pile capacity in cohesionless soils.Key words: driven piles, residual load, toe resistance, shaft resistance.
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Mori, Nobuhiro, Yasuhiro Kawahara, Tomokazu Tsuchiya, Kosuke Sekine, Takao Hara, and Teruhiko Takakura. "Analysis of driving pressure using ventilator management database in ARDS." Iryou kikigaku (The Japanese journal of medical instrumentation) 89, no. 6 (2019): 487–93. http://dx.doi.org/10.4286/jjmi.89.487.

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Dissertations / Theses on the topic "Driving database"

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Rasheed, Yasser. "A database solution for scientific data from driving simulator studies." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-70435.

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Many research institutes produce a huge amount of data. It was said by someone that “We are drowning in data, but starving of information”. This is particularly true for scientific data. The needs and the advantages of being able to search data from different experiments are increasing in order to look for differences and similarities among them and thus doing Meta studies. A Meta-study is the method that takes data from different independent studies and integrate them using statistical analysis. If data is well described and data access is flexible then it is possible to establish unexpected relationships among data. It also helps in the re-using of data from studies that have already been conducted which saves time, money and resources. In this thesis, we explore at the ways to store data from experiments and to make finding cross-experiments more efficient. The main aim of this thesis work is to propose a database solution for storing time series data generated by different simulators and to investigate the feasibility of using it with ICAT. ICAT is a metadata system used for searching and browsing of scientific data. This thesis has been completed in two steps. The first step is aimed at proposing an efficient database solution for storing time series data. The second step is aimed at investigating the feasibility of using ICAT and proposed database solution together. We found out that it is feasible to use ICAT as a metadata system for scientific studies. Since it is free and open source, it can be linked to any system and customized according to the needs.
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Tan, Kaige. "Building verification database and extracting critical scenarios for self-driving car testing on virtual platform." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263927.

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This degree project, conducted at Volvo Cars, investigates a method about how to build a test database for an Autonomous Driving (AD) function on a virtual platform and how to extract critical scenarios from the test database to finish test cases reduction through optimization. The virtual platform under study is the model-in-the-loop (MIL) based Simulation Platform Active Safety (SPAS) environment and the optimization tool being used is modeFrontier. The analyzing process, in which three levels of abstraction for scenarios are proposed in order to fulfill all requirements for an AD function, is followed in the project to build the test database. Application is carried out to transform requirements from a specific Operational Design Domain (ODD) and linguistic representation into a test suite which contains concrete scenarios and test cases. A meta-model is built to help analyze system structure and parameter requirements in the level of logical scenarios. The practicability of a scenario-based approach for the design of AD function test cases generation is demonstrated with the example of building Traffic Congestion Support (TCS) test database. Obtaining the test database and the successful analysis of parameters for the TCS function on the MIL platform lead to the main goal of the thesis project, which is finding edge cases in the test database by optimizing objective functions. By defining the objective functions and building the workflow in modeFrontier after trying with different methods, the optimization process is implemented with two different algorithms separately. pilOPT is evaluated as a better solution for AD function than Multi-Objective Simulated Annealing (MOSA) in terms of computational time and edge cases finding. In addition, a noise model is added to ideal sensor model in SPAS to study the influence of noise in real test track. The result shows a big difference in Time-toCollision value, which is a defined objective function in the project. This indicates more test cases are deteriorated to critical scenario if noise is taken into consideration, which shows the influence of noise cannot be neglected during testing.
Detta examensarbete, genomfört hos Volvo Cars, undersöker en uppbyggnadsmetod av en testdatabas för Autonomous Driving (AD) på en virtuell plattform och hur man bör extrahera kritiska scenarier från testdatabasen för att reducera antalet testfall genom optimering. Den aktuella virtuella plattformen är den model-in-the-loop (MIL) baserade Simulation Platform Active Safety (SPAS) miljön och optimeringsverktyget som användes är modeFrontier. Analysprocessen, i vilken tre abstraktionsnivåer för scenarier är föreslagna i syfte att satisfiera alla kraven för AD, redogörs för i detta projekt. Tillämpning har genomförts för att transformera krav från en specifik Operational Design Domain (ODD) samt lingvistisk representation till en testsvit som innehåller konkreta scenarier och testfall. En metamodell har konstruerats för att assistera med analysen av systemstrukturen och parameterkraven i nivån av logiska scenarier. Genomförbarheten av en scenariobaserad infallsvinkel för designen av AKF-testfall demonstreras med exemplet av konstruktionen av Traffic Congestion Support (TCS)- testdatabasen. Erhållandet av testdatabasen och den framgångsrika analysen av parametrarna för TCSfunktionen på MIL-plattformen ledde till det huvudsakliga målet med examenarbetet, vilket var att identifiera kantfall i testdatabasen genom att optimera objektfunktioner. Genom att definiera objektfunktionerna och konstruera arbetsflödet i modeFrontier efter flertalet försök med olika metoder, implementerades optimeringsprocessen med tvåseparata algoritmer. pilOPT evalueras som en bättre lösning för AD jämfört med Multi-Objective Simulated Annealing (MOSA) med avseende på beräkningstid och identifiering av kantfall. Dessutom har brus adderats till den ideala sensormodellen i SPAS för att studera inflytandet av brus i en verklig testmiljö. Resultaten visar på en stor skillnad i tid-till-kollisionsvärde, vilket är en väldefinierad objektfunktion i projektet. Detta indikerar att fler testfall har försämrats till ett kritiskt scenario om brus tas man tar hänsyn till brus, vilket visar på att inflytandet av brus inte kan försummas under testning.
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NAKAMURA, Satoshi, Kazuya TAKEDA, and Masakiyo FUJIMOTO. "CENSREC-3: An Evaluation Framework for Japanese Speech Recognition in Real Car-Driving Environments." Institute of Electronics, Information and Communication Engineers, 2006. http://hdl.handle.net/2237/15050.

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Šimoňáková, Sabína. "Detekce stresu a únavy v komplexních datech řidiče." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442500.

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Main aim of our thesis is fatigue and stress detection from biological signals of a driver. Introduction contains information on published methods of detection and thoroughly informs readers about theoretical background necessary for our thesis. In the practical application we have firstly worked with a database of measured rides and subsequently chose their most relevant sections. Extraction and selection of features followed afterward. Five different classification models for tiredness and stress detection were used in the thesis and prediction was based on actual data. Lastly, the final section compares the best model of our thesis with the already published results.
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Borkar, Amol. "Multi-viewpoint lane detection with applications in driver safety systems." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/43752.

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The objective of this dissertation is to develop a Multi-Camera Lane Departure Warning (MCLDW) system and a framework to evaluate it. A Lane Departure Warning (LDW) system is a safety feature that is included in a few luxury automobiles. Using a single camera, it performs the task of informing the driver if a lane change is imminent. The core component of an LDW system is a lane detector, whose objective is to find lane markers on the road. Therefore, we start this dissertation by explaining the requirements of an ideal lane detector, and then present several algorithmic implementations that meet these requirements. After selecting the best implementation, we present the MCLDW methodology. Using a multi-camera setup, MCLDW system combines the detected lane marker information from each camera's view to estimate the immediate distance between the vehicle and the lane marker, and signals a warning if this distance is under a certain threshold. Next, we introduce a procedure to create ground truth and a database of videos which serve as the framework for evaluation. Ground truth is created using an efficient procedure called Time-Slicing that allows the user to quickly annotate the true locations of the lane markers in each frame of the videos. Subsequently, we describe the details of a database of driving videos that has been put together to help establish a benchmark for evaluating existing lane detectors and LDW systems. Finally, we conclude the dissertation by citing the contributions of the research and discussing the avenues for future work.
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Burgoyne, John. "Stochastic processes and database-driven musicology." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=107704.

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For more than a decade, music information science and musicology have been at what Nicholas Cook has described as a 'moment of opportunity' for collaboration on database-driven musicology. The literature contains relatively few examples of mathematical tools that are suitable for analysing temporally structured data like music, however, and there are surprisingly few large databases of music that contain information at the semantic levels of interest to musicologists. This dissertation compiles a bibliography of the most important concepts from probability and statistics for analysing musical data, reviews how previous researchers have used statistics to study temporal relationships in music, and presents a new corpus of carefully curated chord labels from more than 1000 popular songs from the latter half of the twentieth century, as ranked by Billboard magazine's Hot 100 chart. The corpus is based on a careful sampling methodology that maintained cost efficiency while ensuring that the corpus is well suited to drawing conclusions about how harmonic practises may have evolved over time and to what extent they may have affected songs' popularity. This dissertation also introduces techniques new to the musicological community for analysing databases of this size and scope, most importantly the Dirichlet-multinomial distribution and constraint-based structure learning for causal Bayesian networks. The analysis confirms some common intuitions about harmonic practises in popular music and suggests several intriguing directions for further research.
Depuis plus d'une décennie, la science de l'information de la musique et la musicologie sont à ce que Nicholas Cook décrit comme "un moment clé" en ce qui concerne une collaboration pouvant mener à une réelle science de la musique fondé sur l'analyse de large quantité de données. Toutefois, la littérature comporte rélativement peu d'exemples d'outils mathématiques qui conviendraient à l'analyse des données qui, comme les données musicales, ont des dépendances temporelles, et il y a très peu de bases de données qui contiennent des informations avec la richesse sémantique intéressant d'ordinaire les musicologues. Cette thèse assemble une bibliographie des concepts les plus importants de la probabilité et de la statistique pour analyser les données musicales, revisite la manière dont les chercheurs précédents se servaient de la statistique pour étudier les rapports temporels, et présente un nouveau corpus soigneusement préparé contenant les transcriptions d'accords pour plus de 1000 chansons populaires de la deuxième moitié du XXe siècle, figurant du "Hot 100" de la revue Billboard. Le corpus résulte d'une méthodologie d'échantillonnage qui optimise les coûts et s'assure que le corpus conviendrait à tirer des conclusions montrant comment les pratiques harmoniques ont pu évoluer au fils du temps et dans quelle mesure elles peuvent avoir une incidence sur la popularité des chansons. Cette thèse introduit aussi quelques techniques qui sont nouvelles en musicologie pour analyser les bases de données d'une telle taille et d'une telle portée; les plus importantes parmi ces techniques sont la distribution multinomiale de Dirichlet et l'apprentissage via contraintes de structure des réseaux causaux de Bayes. L'analyse confirme quelques intuitions courantes concernant les pratiques harmoniques de la musique populaire et suggère quelques voies intéressantes pour la recherche à venir.
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Naumann, Felix. "Quality-driven query answering for integrated information systems /." Berlin [u.a.] : Springer, 2002. http://www.loc.gov/catdir/enhancements/fy0817/2002023684-d.html.

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Guo, Dahai. "Creating Geo-Specific Road Databases from Aerial Photos for Driving Simulation." Doctoral diss., University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2789.

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Geo-specific road database development is important to a driving simulation system and a very labor intensive process. Road databases for driving simulation need high resolution and accuracy. Even though commercial software is available on the market, a lot of manual work still has to be done when the road crosssectional profile is not uniform. This research deals with geo-specific road databases development, especially for roads with non-uniform cross sections. In this research, the United States Geographical Survey (USGS) road information is used with aerial photos to accurately extract road boundaries, using image segmentation and data compression techniques. Image segmentation plays an important role in extracting road boundary information. There are numerous methods developed for image segmentation. Six methods have been tried for the purpose of road image segmentation. The major problems with road segmentation are due to the large variety of road appearances and the many linear features in roads. A method that does not require a database of sample images is desired. Furthermore, this method should be able to handle the complexity of road appearances. The proposed method for road segmentation is based on the mean-shift clustering algorithm and it yields a high accuracy. In the phase of building road databases and visual databases based on road segmentation results, the Linde-Buzo-Gray (LBG) vector quantization algorithm is used to identify repeatable cross section profiles. In the phase of texture mapping, five major uniform textures are considered - pavement, white marker, yellow marker, concrete and grass. They are automatically mapped to polygons. In the chapter of results, snapshots of road/visual database are presented.
Ph.D.
Department of Electrical and Computer Engineering
Engineering and Computer Science
Computer Engineering
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Heath, Michael Adam. "Asynchronous Database Drivers." BYU ScholarsArchive, 2010. https://scholarsarchive.byu.edu/etd/2387.

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Existing database drivers use blocking socket I/O to exchange data with relational database management systems (RDBMS). To concurrently send multiple requests to a RDBMS with blocking database drivers, a separate thread must be used for each request. This approach has been used successfully for many years. However, we propose that using non-blocking socket I/O is faster and scales better under load. In this paper we introduce the Asynchronous Database Connectivity in Java (ADBCJ) framework. ADBCJ provides a common API for asynchronous RDBMS interaction. Various implementations of the ADBCJ API are used to show how utilizing non-blocking socket I/O is faster and scales better than using conventional database drivers and multiple threads for concurrency. Our experiments show a significant performance increase when using non- blocking socket I/O for asynchronous RDBMS access while using a minimal number of OS threads. Non-blocking socket I/O enables the ability to pipeline RDBMS requests which can improve performance significantly, especially over high latency networks. We also show the benefits of asynchronous database drivers on different web server architectures.
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Kallem, Aditya. "Visualization for Verification Driven Learning in Database Studies." ScholarWorks@UNO, 2010. http://scholarworks.uno.edu/td/99.

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This thesis aims at developing a data visualization tool to enhance database learning based on the Verification Driven Learning (VDL) model. The goal of the VDL model is to present abstract concepts in the contexts of real-world systems to students in the early stages of computer science program. In this project, a personnel/training management system has been turned into a learning platform by adding a number of features for visualization and quizzing. We have implemented various tactics to visualize the data manipulation and data retrieval operations in database, as well as the message contents in data messaging channels. The results of our development have been utilized in eight learning cases illustrating the applications of our visualization tool. Each of these learning cases were made by systematically implanting bugs in a functioning component; the students are assigned to identify the bugs and at the same time to learn the structure of the software system active
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Books on the topic "Driving database"

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(Firm), CiA Training, ed. ECDL/ICDL advanced AM5 Database using Microsoft Access. Sunderland: CiA Training Ltd, 2005.

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McLaughlin, Shane B., and Jonathan M. Hankey. Naturalistic Driving Study: Linking the Study Data to the Roadway Information Database. Washington, D.C.: Transportation Research Board, 2015. http://dx.doi.org/10.17226/22200.

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service), ScienceDirect (Online, ed. Next generation datacenters in financial services: Driving extreme efficiency and effective cost savings. Burlington, MA: Elsevier, 2009.

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ECDL module 5. London: Springer, 2000.

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Morrison, Mike. Database-driven web sites. 2nd ed. Australia: Course Technology, 2003.

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Joline, Morrison, ed. Database-driven web sites. 2nd ed. Boston, Mass: Course Technology, 2003.

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Tillmann, George. Usage-Driven Database Design. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2722-0.

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Valentine, Thomas. Database-Driven Web Development. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-5970-2.

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Jerke, Noel, and Darin Beard. Building Database-Driven Flash Applications. Berkeley, CA: Apress, 2004. http://dx.doi.org/10.1007/978-1-4302-1112-9.

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Patrick, Gannon, ed. Building database-driven web catalogs. New York: McGraw-Hill, 1998.

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Book chapters on the topic "Driving database"

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Zahay, Debra. "Successful B2B Customer Database Management." In Revolution in Marketing: Market Driving Changes, 110. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11761-4_50.

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Lockemann, Peter C., Alfons Kemper, and Guido Moerkotte. "Future database technology: Driving forces and directions." In Database Systems of the 90s, 15–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-53397-4_30.

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Liu, Zhidan, Junhong Zheng, Zengyang Gong, Haodi Zhang, and Kaishun Wu. "Exploiting Multi-source Data for Adversarial Driving Style Representation Learning." In Database Systems for Advanced Applications, 491–508. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73194-6_33.

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Robinson, Garry. "The Access Protection and Security Driving Instructions." In Real World Microsoft Access Database Protection and Security, 1–22. Berkeley, CA: Apress, 2004. http://dx.doi.org/10.1007/978-1-4302-0793-1_1.

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Chaczko, Zenon, Marek Kulbacki, Grzegorz Gudzbeler, Mohammad Alsawwaf, Ilya Thai-Chyzhykau, and Peter Wajs-Chaczko. "Exploration of Explainable AI in Context of Human-Machine Interface for the Assistive Driving System." In Intelligent Information and Database Systems, 507–16. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42058-1_42.

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Mohamed, A. Razia, P. Vineeth Kumar, S. Abhilash, C. N. Ravishankar, and Leela Edwin. "Design and Development of an Online Database Management System (AGRI-TECHBASE): For Agricultural Technologies of ICAR." In Driving the Economy through Innovation and Entrepreneurship, 869–77. India: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-0746-7_71.

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Ahmad, Norita, Fariedah Maarof, Elgilani Eltahir Elshareif, and Jade Opulencia. "A Web-Based Benchmarking Tool and Database for SMEs: Research in Progress." In Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy, 631–37. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-43434-6_54.

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Themann, P., A. Pütz, A. Zlocki, and L. Eckstein. "Database of relevant traffic scenarios as a tool for the development and validation of automated driving." In Advanced Vehicle Control AVEC’16, 489–96. CRC Press/Balkema, P.O. Box 11320, 2301 EH Leiden, The Netherlands, e-mail: Pub.NL@taylorandfrancis.com, www.crcpress.com – www.taylorandfrancis.com: Crc Press, 2016. http://dx.doi.org/10.1201/9781315265285-78.

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Hazans, Mihails. "Emigration from Latvia: A Brief History and Driving Forces in the Twenty-First Century." In IMISCOE Research Series, 35–68. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12092-4_3.

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Abstract In recent years, Latvia has established itself as one of the top two countries with the most intensive emigration among EU/EFTA member states. This chapter starts by describing the demographic context and the scale of emigration post-2000, followed by a brief history of the main population flows (migration, refugees and deportation) from and to Latvia in the twentieth century. It then offers a more detailed analysis of emigration during the first 15 years of the twenty-first century including a closer look at the four waves of recent emigration: (i) the pre-EU accession wave, 2000–2003; (ii) the post-accession wave, 2004–2008; (iii) the crisis-driven wave, 2009–2010; and (iv) the post-crisis wave, 2011–2016. For each wave, description of the economic and social context is given within a conceptual framework using insights from human capital theory, the new economic theory of migration, network theory and migration systems theory. Institutional factors are also emphasised. Together with some survey-based evidence, this leads to a set of hypotheses about the nature of the four emigration waves. Our own compilation of data from receiving countries (which reveals problems with Latvia’s official migration statistics) is used for documenting the dynamics of the scale and main destinations of this emigration. Empirical analysis of the changes in the reasons for and intended duration of emigration, its effects on the structure and demographic potential of the population and changes in emigrant profiles and selectivity with respect to human capital and ethnicity is based on a number of independent data sources, including the Latvian Labour Force Survey (2000–2015), the Database of Immigrants in OECD Countries (DIOC 2010/2011), and The Emigrant Communities of Latvia survey conducted worldwide in 2014.
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Maurer, Marcus, Jörg Haßler, and Thomas Holbach. "Database-Driven Content Analysis." In Political Communication in the Online World, 170–82. New York, NY : Routledge, 2016. | Series: Routledge research in political communication ; 13: Routledge, 2015. http://dx.doi.org/10.4324/9781315707495-12.

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Conference papers on the topic "Driving database"

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Mikolajetz, Anna, Matthias J. Henning, Axel Tenzer, Robert Zobel, Josef F. Krems, and Tibor Petzoldt. "Curve Negotiation: Identifying Driver Behavior Around Curves with the Driver Performance Database." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2009. http://dx.doi.org/10.17077/drivingassessment.1348.

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Seaman, Sean, Joonbum Lee, Bobbie Seppelt, Linda Angell, Bruce Mehler, and Bryan Reimer. "It’s All in the Timing: Using the Attend Algorithm to Assess Texting in the Nest Naturalistic Driving Database." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2017. http://dx.doi.org/10.17077/drivingassessment.1665.

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Zhang, Hui, Xinping Yan, Chaozhong Wu, Song Gao, and Hu Lei. "Design and Implementation of Driving Behavior Analysis Database." In 2010 2nd International Workshop on Database Technology and Applications (DBTA). IEEE, 2010. http://dx.doi.org/10.1109/dbta.2010.5658945.

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Zeng, Yufan, Xichan Zhu, Zhixiong Ma, and Xiaoyu Sun. "Critical Driving Scenarios Extraction Optimization Method Based on China-FOT Naturalistic Driving Study Database." In Intelligent and Connected Vehicles Symposium. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2018. http://dx.doi.org/10.4271/2018-01-1628.

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Lee, Kangwon, and Huei Peng. "Identification of a Longitudinal Human Driving Model for Adaptive Cruise Control Performance Assessment." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-32089.

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The main purpose of this paper is to develop a longitudinal human driving model that is accurate enough for the performance evaluation of adaptive cruise control systems. Six driver models were evaluated based on selected data from two vehicle motion databases—the SAVME database and the ICCFOT database, both created at the University of Michigan Transportation Research Institute (UMTRI). Among the models we evaluated, the Gipps’ model was found to be the most promising and was further analyzed. A modified version of the model was suggested and evaluated. The modified model was implemented in a microscopic traffic simulator and was found to produce results that agree with macroscopic traffic behavior very well.
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Hsu, Wei-Yen, Kun-Sin Lien, Yu-Chan Wang, Yu-Ting Zheng, and Guan-Han Li. "Real-Time Driving Monitor System: Combined Cloud Database with GPS." In 2016 49th Hawaii International Conference on System Sciences (HICSS). IEEE, 2016. http://dx.doi.org/10.1109/hicss.2016.219.

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Ma, Lin, Dana Van Aken, Ahmed Hefny, Gustavo Mezerhane, Andrew Pavlo, and Geoffrey J. Gordon. "Query-based Workload Forecasting for Self-Driving Database Management Systems." In SIGMOD/PODS '18: International Conference on Management of Data. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3183713.3196908.

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Ma, Lin, William Zhang, Jie Jiao, Wuwen Wang, Matthew Butrovich, Wan Shen Lim, Prashanth Menon, and Andrew Pavlo. "MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems." In SIGMOD/PODS '21: International Conference on Management of Data. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3448016.3457276.

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Jeong-tae Park, Jun-beom Park, and Jung-ha Kim. "The research on establishment of database for autonomous-driving in downtown." In 2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI). IEEE, 2015. http://dx.doi.org/10.1109/urai.2015.7358862.

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Zhang, Zhiqiang, Juan Shi, Kuiyuan Guo, and Jiyu Wang. "Research on Construction Method and Application of Autonomous Driving Test Scenario Database." In 20th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2020. http://dx.doi.org/10.1061/9780784482933.027.

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