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1

Bergel, Alexandre. Agile Artificial Intelligence in Pharo. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5384-7.

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2

Briglia, Peter M. ITS evaluation framework: Phase 2. [Olympia]: Washington State Dept. of Transportation, 2007.

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3

Owen, Stephen R. Arizona Intelligent Vehicle Research Program: Phase three, 2002-2003. [Phoenix, Ariz: Arizona Dept. of Transportation, 2004.

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4

Steinberg, Richard. The 4 phase man. New York: Doubleday, 2000.

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5

Dailey, Daniel J. TrafficTV, phase 2. [Olympia, Wash.]: Washington State Dept. of Transportation, 2006.

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6

Hatcher, S. Gregory. Incorporating ITS into transportation planning: Phase 1 final report. McLean, Va: Mitretek Systems, 1997.

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7

L, Milner James, Nelson Gary G, United States. Federal Highway Administration, and Mitretek Systems, eds. Incorporating ITS into transportation planning: Phase 1 final report. McLean, Va: Mitretek Systems, 1997.

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8

Hatcher, S. Gregory. Incorporating ITS into transportation planning: Phase 1 final report. McLean, Va: Mitretek Systems, 1997.

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9

Slaughter, David C. Intelligent herbicide application system for reduced herbicide vegetation control: Phase 2, commercialization. Sacramento, CA: California Dept. of Transportation, Division of Research and Innovation, 2008.

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10

Domeshek, Eric A. Intelligent tutoring system for teaching battlefield command reasoning skills: Phase I final report. Alexandria, VA: U.S. Army Research Institute for the Behavioral and Social Sciences, 2002.

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11

Fein, Ph D. Robert A. Introduction Intelligence Science Board Study on Educing Information: Phase 1 Report. Washington, D.C.: NDIC Press, 2006.

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12

Domeshek, Eric A. Phase II final report on an intelligent tutoring system for teaching battlefield command reasoning skills. Alexandria, VA: U.S. Army Research Institute for the Behavioral and Social Sciences, 2004.

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13

Rakha, Hesham. Transit signal priority project, phase II: Field and simulation evaluation results. Charlottesville, Va: Virginia Transportation Research Council, 2006.

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14

Maze, T. H. Intelligent transportation systems (ITS) and commercial vehicle operations (CVO) interstate cooperation for implementation of ITS-CVO functions: Institutional opportunities and barriers : phase 1 report. Ames, Iowa: Midwest Transportation Center, 1995.

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15

Barski, Marek. Metody homogenizacji inteligentnych ośrodków dwufazowych umacnianych cząstkami: Homogenization methods of smart two-phase materials reinforced by particles = Methoden der Homogenisierung intelligenter mit Partikeln befestigter zweiphasiger Zentren. Kraków: Wydawnictwo PK, 2011.

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16

United States. National Aeronautics and Space Administration., ed. Intelligent Robotic Systems Study (IRSS): Phase IV, final report. Denver, Colo: Martin Marietta Astronautics Group, 1991.

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17

Intelligent Robotic Systems Study (IRSS): Phase III, final report. Denver, Colo: Martin Marietta Astronautics Group, 1991.

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18

United States. National Aeronautics and Space Administration., ed. Intelligent Robotic Systems Study (IRSS): Phase II, final report. Denver, Colo: Martin Marietta Astronautics Group, 1990.

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19

The 4 Phase Man. New York: Random House Publishing Group, 2009.

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20

America, ITS, and United States. Dept. of Transportation., eds. ITS architecture development program: Phase I, summary report. Washington, D.C: ITS America, 1994.

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21

Steinberg, Richard. The 4 Phase Man (Bookcassette(r) Edition). Bookcassette, 2000.

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22

National performance review: Phase II initiatives, September 1995 : an Intelligence Community report. Washington, DC: United States Intelligence Community Team, 1995.

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23

Bergel, Alexandre. Agile Artificial Intelligence in Pharo: Implementing Neural Networks, Genetic Algorithms, and Neuroevolution. Apress, 2020.

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24

1976-, Aarabi Parham, ed. Phase-based speech processing. Singapore: World Scientific, 2006.

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25

Shi, Guangji. Phase-based speech processing. 2006.

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26

1967-, Smith Brian L., McGhee Catherine C, Virginia Transportation Research Council, Virginia. Dept. of Transportation., and University of Virginia. Center for Transportation Studies., eds. Preparing to use vehicle infrastructure integration in transportation operations: Phase I. Charlottesville, Va: Virginia Transportation Research Council, 2007.

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27

(Editor), Moshe Schein, and Leslie Wise (Editor), eds. Cytokines and the Abdominal Surgeon (Medical Intelligence Unit). Landes Bioscience, 1998.

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28

Center for Strategic Intelligence Research (U.S.), United States. Intelligence Science Board., and Federation of American Scientists, eds. Educing information: Interrogation--science and art : foundations for the future : phase 1 report. Washington, DC: Center for Strategic Intelligence Research, National Defense Intelligence College, 2006.

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29

Anscomb, Anne. Outsourcing in Drug Development: The Contract Research Market from Preclinical to Phase III (Kalorama Information Market Intelligence Report). Find/SVP, 2003.

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30

Gibson, Rachel K. When the Nerds Go Marching In. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780195397789.001.0001.

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When the Nerds Go Marching In shows how digital technology has moved from the margins to the mainstream of campaign and election organization in contemporary democracies. Combining an extensive review of existing literature and comparative data sources with original survey evidence and web content analysis of digital campaign content across four nations—the United Kingdom, Australia, France, and the United States—the book maps the key shifts in the role and centrality of the internet in election campaigns over a twenty-year period. The chapters reveal how these countries have followed a four-phase model of digital campaign development which begins with experimentation, and is followed by a period of standardization and professionalization. Subsequent phases focus on increasingly strategic activities around the mobilization of activists and supporters, before switching to micro-targeted mobilizing of individual voters. The changes are mapped over time in each country from the perspective of both the campaigners (supply side), and that of voters (demand side), and the four nations are compared in terms of how far and fast they have moved through the developmental cycle. As well as providing the most comprehensive narrative charting the evolution of digital campaigning from its inception in the mid-1990s, the book also offers important insights into the national conditions that have been most conducive to its diffusion. Finally, based on the findings from the most recent phase of development, the book speculates on the future direction for political campaigns as they increasingly rely on digital tools and artificial intelligence for direction and decision-making during elections.
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31

Davies, Tim, Stephen B. Walker, Mor Rubinstein, and Fernando Luis Perini. The State of Open Data: Histories and Horizons. African Minds and IDRC, 2019. http://dx.doi.org/10.47622/9781928331957.

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Its been ten years since open data first broke onto the global stage. Over the past decade, thousands of programmes and projects around the world have worked to open data and use it to address a myriad of social and economic challenges. Meanwhile, issues related to data rights and privacy have moved to the centre of public and political discourse. As the open data movement enters a new phase in its evolution, shifting to target real-world problems and embed open data thinking into other existing or emerging communities of practice, big questions still remain. How will open data initiatives respond to new concerns about privacy, inclusion, and artificial intelligence? And what can we learn from the last decade in order to deliver impact where it is most needed? The State of Open Data brings together over 60 authors from around the world to address these questions and to take stock of the real progress made to date across sectors and around the world, uncovering the issues that will shape the future of open data in the years to come.
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32

Érdi, Péter. Ranking. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190935467.001.0001.

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As humans, we like to see who is stronger, richer, better, or cleverer. As we also (1) love lists, (2) are competitive, and (3) are jealous of other people, we like ranking. We can rank some situations objectively: students ranked by their heights reflects objectivity. However, many “top-10” (or 21, 33, etc.) lists are based on subjective categorization and give only the illusion of objectivity. In fact, we don’t always want to be seen objectively since we don’t mind having a better image or rank than we deserve. The book applies scientific theories to everyday experience by raising and answering questions like: Are college ranking lists objective? How do we rank and rate countries based on their fragility, level of corruption, or even happiness? How do we find the most relevant webpages? How are employees ranked? The book is offered to people whose neighbor has a fancier car; employees who are being ranked by their supervisors; managers who are involved in ranking but may have qualms about the process; businesspeople interested in creating better visibility for their companies; scientists, writers, artists, and other competitors who would like to see themselves at the top of a success list; and college students who are just preparing to enter a new phase of social competition. Readers will engage in an intellectual adventure to better understand the difficulties of navigating between objectivity and subjectivity and to better identify and modify their place in real and virtual communities by combining human and computational intelligence.
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33

Aarabi, Parham, Guangji Shi, Maryam Modir Shanechi, and Seyed Alireza Rabi. Phased-Based Speech Processing. World Scientific Publishing Company, 2005.

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34

Aarabi, Parham, Guangji Shi, Maryam Modir Shanechi, and Seyed Alireza Rabi. Phased-Based Speech Processing. World Scientific Publishing Company, 2005.

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