Relevant bibliographies by topics / SLAM (Computer program language)

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

Academic literature on the topic 'SLAM (Computer program language)'

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Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "SLAM (Computer program language)"

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Radune, Maya, Alex Radune, F. Assous, and Michael Zinigrad. "Investigation of a Mathematical Model of High-Temperature Diffusion Controlled Heterogeneous Reaction between Metal and Oxide Melts." Defect and Diffusion Forum 297-301 (April 2010): 1475–80. http://dx.doi.org/10.4028/www.scientific.net/ddf.297-301.1475.

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A deterministic computational model of high-temperature heterogeneous re- action between metal and oxide melts has been developed. Transport of reagents and products of reaction occur simultaneously both by diusion and by laminar natural con- vection of the melting metal and oxide uxes. The convection-diusion equations have been numerically solved by a nite-dierences time-implicit discretization scheme. The model was implemented by program which had been written in C# language. The com- putations have been performed for desulfurization reaction between liquid steel and slag phases.The computed results agree well with the results which were found by experimen- tal methods.
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Harris, Kisa K., Frances Henderson, Wendy B. White, Amel Mohamed, and Asoka Srinivasan. "The Jackson Heart Study: Preparing African American High School Students for Health Careers and Research." Ethnicity & Disease 30, no. 1 (January 16, 2020): 25–32. http://dx.doi.org/10.18865/ed.30.1.25.

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In 1999, Tougaloo College (TC), located in Jackson, Mississippi, was charged, as a part of its role in the Jackson Heart Study (JHS), with creating a pool of well-trained high school students who, upon entering college, could successfully complete undergraduate and graduate or professional degrees in the health professions, biomedical research, and public health. TC identified the following educational challenges experienced by Mississippi high school students: inadequate exposure to reading, writing, logic, and quantitative skills; inadequate course work in science and mathematics; lack of mentors and role models in science-related fields as well as for exploration and identification of career options in the health professions and biomedical research. To this end, the JHS Undergraduate Training and Educa­tion Center (JHS UTEC) developed three four-week summer workshops in Science, Language Arts, and Mathematics (SLAM) for high school students in grades 9 through 11. Since SLAM’s inception, more than 900 students have completed the program, and more than 90% have enrolled in college. In addition, according to National Student Clearinghouse and participant-reported data, many of the SLAM participants have earned not only undergraduate degrees in science, but also graduate degrees in a health-related and STEM fields. This article details the SLAM curricula and strategies for recruiting, selecting, training, and retain­ing high school students; we also present data to illustrate the success of the SLAM program. Ethn Dis. 2020;30(1):25-32; doi:10.18865/ed.30.1.25
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Karn, Helen E., and MacEnglish. "Pronunciation Plus (Computer Program)." TESOL Quarterly 30, no. 1 (1996): 176. http://dx.doi.org/10.2307/3587618.

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Solomon, Gabriela R., and Ford Language Institute. "The American Accent Program (Computer Program, Version 4.0)." TESOL Quarterly 27, no. 4 (1993): 774. http://dx.doi.org/10.2307/3587425.

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Wu, Yakun, Li Luo, Shujuan Yin, Mengqi Yu, Fei Qiao, Hongzhi Huang, Xuesong Shi, Qi Wei, and Xinjun Liu. "An FPGA Based Energy Efficient DS-SLAM Accelerator for Mobile Robots in Dynamic Environment." Applied Sciences 11, no. 4 (February 18, 2021): 1828. http://dx.doi.org/10.3390/app11041828.

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The Simultaneous Localization and Mapping (SLAM) algorithm is a hotspot in robot application research with the ability to help mobile robots solve the most fundamental problems of “localization” and “mapping”. The visual semantic SLAM algorithm fused with semantic information enables robots to understand the surrounding environment better, thus dealing with complexity and variability of real application scenarios. DS-SLAM (Semantic SLAM towards Dynamic Environment), one of the representative works in visual semantic SLAM, enhances the robustness in the dynamic scene through semantic information. However, the introduction of deep learning increases the complexity of the system, which makes it a considerable challenge to achieve the real-time semantic SLAM system on the low-power embedded platform. In this paper, we realized the high energy-efficiency DS-SLAM algorithm on the Field Programmable Gate Array (FPGA) based heterogeneous platform through the optimization co-design of software and hardware with the help of OpenCL (Open Computing Language) development flow. Compared with Intel i7 CPU on the TUM dataset, our accelerator achieves up to 13× frame rate improvement, and up to 18× energy efficiency improvement, without significant loss in accuracy.
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McMinn, Mark R., and James D. Foster. "A Computer Program to Teach Nonsexist Language." Teaching of Psychology 18, no. 2 (April 1991): 115–17. http://dx.doi.org/10.1207/s15328023top1802_16.

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Reps and Teitelbaum. "Language Processing in Program Editors." Computer 20, no. 11 (November 1987): 29–40. http://dx.doi.org/10.1109/mc.1987.1663414.

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Yalcin, Hatice, and Murat Demirekin. "Training Program Supporting Language Acquisition." International Journal of Modern Education and Computer Science 13, no. 3 (June 8, 2021): 1–12. http://dx.doi.org/10.5815/ijmecs.2021.03.01.

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Baniassad, Elisa, and Clayton Myers. "An exploration of program as language." ACM SIGPLAN Notices 44, no. 10 (October 25, 2009): 547–56. http://dx.doi.org/10.1145/1639949.1640132.

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Underwood, John, Keith Cameron, Theo Bongaerts, Pieter de Haan, Sylvia Lobbe, and Herman Wekker. "Computer Assisted Language Learning: Program Structure and Principles." Modern Language Journal 74, no. 4 (1990): 511. http://dx.doi.org/10.2307/328534.

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Dissertations / Theses on the topic "SLAM (Computer program language)"

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Cornwall, Maxwell W. "MEEBS a model for multi-echelon evaluation by simulation /." Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA237099.

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Thesis (M.S. in Management)--Naval Postgraduate School, June 1990.
Thesis Advisor(s): McMasters, Alan W. ; Bailey, Michael P. "June 1990." Description based on signature page as viewed on October 21, 2009. DTIC Identifier(s): Computerized simulation, logistics management. Author(s) subject terms: Multi-echelon, simulation, SLAM II, models. Includes bibliographical references (p. 142-147). Also available in print.
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Kiang, Kai-Ming Mechanical &amp Manufacturing Engineering Faculty of Engineering UNSW. "Natural feature extraction as a front end for simultaneous localization and mapping." Awarded by:University of New South Wales. School of Mechanical and Manufacturing Engineering, 2006. http://handle.unsw.edu.au/1959.4/26960.

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This thesis is concerned with algorithms for finding natural features that are then used for simultaneous localisation and mapping, commonly known as SLAM in navigation theory. The task involves capturing raw sensory inputs, extracting features from these inputs and using the features for mapping and localising during navigation. The ability to extract natural features allows automatons such as robots to be sent to environments where no human beings have previously explored working in a way that is similar to how human beings understand and remember where they have been. In extracting natural features using images, the way that features are represented and matched is a critical issue in that the computation involved could be wasted if the wrong method is chosen. While there are many techniques capable of matching pre-defined objects correctly, few of them can be used for real-time navigation in an unexplored environment, intelligently deciding on what is a relevant feature in the images. Normally, feature analysis that extracts relevant features from an image is a 2-step process, the steps being firstly to select interest points and then to represent these points based on the local region properties. A novel technique is presented in this thesis for extracting a small enough set of natural features robust enough for navigation purposes. The technique involves a 3-step approach. The first step involves an interest point selection method based on extrema of difference of Gaussians (DOG). The second step applies Textural Feature Analysis (TFA) on the local regions of the interest points. The third step selects the distinctive features using Distinctness Analysis (DA) based mainly on the probability of occurrence of the features extracted. The additional step of DA has shown that a significant improvement on the processing speed is attained over previous methods. Moreover, TFA / DA has been applied in a SLAM configuration that is looking at an underwater environment where texture can be rich in natural features. The results demonstrated that an improvement in loop closure ability is attained compared to traditional SLAM methods. This suggests that real-time navigation in unexplored environments using natural features could now be a more plausible option.
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Cunningham, Alexander G. "Scalable online decentralized smoothing and mapping." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51848.

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Many applications for field robots can benefit from large numbers of robots, especially applications where the objective is for the robots to cover or explore a region. A key enabling technology for robust autonomy in these teams of small and cheap robots is the development of collaborative perception to account for the shortcomings of the small and cheap sensors on the robots. In this dissertation, I present DDF-SAM to address the decentralized data fusion (DDF) inference problem with a smoothing and mapping (SAM) approach to single-robot mapping that is online, scalable and consistent while supporting a variety of sensing modalities. The DDF-SAM approach performs fully decentralized simultaneous localization and mapping in which robots choose a relevant subset of variables from their local map to share with neighbors. Each robot summarizes their local map to yield a density on exactly this chosen set of variables, and then distributes this summarized map to neighboring robots, allowing map information to propagate throughout the network. Each robot fuses summarized maps it receives to yield a map solution with an extended sensor horizon. I introduce two primary variations on DDF-SAM, one that uses a batch nonlinear constrained optimization procedure to combine maps, DDF-SAM 1.0, and one that uses an incremental solving approach for substantially faster performance, DDF-SAM 2.0. I validate these systems using a combination of real-world and simulated experiments. In addition, I evaluate design trade-offs for operations within DDF-SAM, with a focus on efficient approximate map summarization to minimize communication costs.
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Joubert, Daniek. "Adaptive occupancy grid mapping with measurement and pose uncertainty." Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/71911.

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Thesis (MSc)--Stellenbosch University, 2012.
ENGLISH ABSTRACT: In this thesis we consider the problem of building a dense and consistent map of a mobile robot’s environment that is updated as the robot moves. Such maps are vital for safe and collision-free navigation. Measurements obtained from a range sensor mounted on the robot provide information on the structure of the environment, but are typically corrupted by noise. These measurements are also relative to the robot’s unknown pose (location and orientation) and, in order to combine them into a world-centric map, pose estimation is necessary at every time step. A SLAM system can be used for this task. However, since landmark measurements and robot motion are inherently noisy, the pose estimates are typically characterized by uncertainty. When building a map it is essential to deal with the uncertainties in range measurements and pose estimates in a principled manner to avoid overconfidence in the map. A literature review of robotic mapping algorithms reveals that the occupancy grid mapping algorithm is well suited for our goal. This algorithm divides the area to be mapped into a regular lattice of cells (squares for 2D maps or cubes for 3D maps) and maintains an occupancy probability for each cell. Although an inverse sensor model is often employed to incorporate measurement uncertainty into such a map, many authors merely state or depict their sensor models. We derive our model analytically and discuss ways to tailor it for sensor-specific uncertainty. One of the shortcomings of the original occupancy grid algorithm is its inability to convey uncertainty in the robot’s pose to the map. We address this problem by altering the occupancy grid update equation to include weighted samples from the pose uncertainty distribution (provided by the SLAM system). The occupancy grid algorithm has been criticized for its high memory requirements. Techniques have been proposed to represent the map as a region tree, allowing cells to have different sizes depending on the information received for them. Such an approach necessitates a set of rules for determining when a cell should be split (for higher resolution in a local region) and when groups of cells should be merged (for lower resolution). We identify some inconsistencies that can arise from existing rules, and adapt those rules so that such errors are avoided. We test our proposed adaptive occupancy grid algorithm, that incorporates both measurement and pose uncertainty, on simulated and real-world data. The results indicate that these uncertainties are included effectively, to provide a more informative map, without a loss in accuracy. Furthermore, our adaptive maps need far fewer cells than their regular counterparts, and our new set of rules for deciding when to split or merge cells significantly improves the ability of the adaptive grid map to mimic its regular counterpart.
AFRIKAANSE OPSOMMING: In hierdie tesis beskou ons die probleem om ’n digte en konsekwente kaart van ’n mobiele robot se omgewing te bou, wat opgedateer word soos die robot beweeg. Sulke kaarte is van kardinale belang vir veilige, botsingvrye navigasie. Metings verkry vanaf ’n sensor wat op die robot gemonteer is, verskaf inligting rakende die struktuur van die omgewing, maar word tipies deur ruis vervorm. Hierdie metings is ook relatief tot die robot se onbekende postuur (posisie en oriëntasie) en, om hulle saam te voeg in ’n wêreldsentriese kaart, is postuurafskatting nodig op elke tydstap. ’n SLAM stelsel kan vir hierdie doeleinde gebruik word. Aangesien landmerkmetings en die beweging van die robot inherent ruiserig is, word die postuurskattings gekarakteriseer deur onsekerheid. Met die bou van ’n kaart moet hierdie onsekerhede in afstandmetings en postuurskattings op ’n beginselvaste manier hanteer word om te verhoed dat te veel vertroue in die kaart geplaas word. ’n Literatuurstudie van karteringsalgoritmes openbaar die besettingsroosteralgoritme as geskik vir ons doel. Die algoritme verdeel die gebied wat gekarteer moet word in ’n reëlmatige rooster van selle (vierkante vir 2D kaarte of kubusse vir 3D kaarte) en onderhou ’n besettingswaarskynlikheid vir elke sel. Alhoewel ’n inverse sensormodel tipies gebruik word om metingsonsekerheid in so ’n kaart te inkorporeer, noem of wys baie outeurs slegs hulle model. Ons herlei ons model analities en beskryf maniere om sensorspesifieke metingsonsekerheid daarby in te sluit. Een van die tekortkominge van die besettingsroosteralgoritme is sy onvermoë om onsekerheid in die postuur van die robot na die kaart oor te dra. Ons spreek hierdie probleem aan deur die opdateringsvergelyking van die oorspronklike besettingsroosteralgoritme aan te pas, om geweegde monsters van die postuuronsekerheidsverdeling (verskaf deur die SLAM stelsel) in te sluit. Die besettingsroosteralgoritme word soms gekritiseer vir sy hoë verbruik van geheue. Tegnieke is voorgestel om die kaart as ’n gebiedsboom voor te stel, wat selle toelaat om verskillende groottes te hê, afhangende van die inligting wat vir hulle verkry is. So ’n benadering noodsaak ’n stel reëls wat spesifiseer wanneer ’n sel verdeel (vir ’n hoër resolusie in ’n plaaslike gebied) en wanneer ’n groep selle saamgevoeg (vir ’n laer resolusie) word. Ons identifiseer teenstrydighede wat kan voorkom as die huidige reëls gevolg word, en pas hierdie reëls aan sodat sulke foute vermy word. Ons toets ons voorgestelde aanpasbare besettingsroosteralgoritme, wat beide metings- en postuuronsekerheid insluit, op gesimuleerde en werklike data. Die resultate dui daarop dat hierdie onsekerhede op ’n effektiewe wyse na die kaart oorgedra word sonder om akkuraatheid prys te gee. Wat meer is, ons aanpasbare kaarte benodig heelwat minder selle as hul reëlmatige eweknieë. Ons nuwe stel reëls om te besluit wanneer selle verdeel of saamgevoeg word, veroorsaak ook ’n merkwaardige verbetering in die vermoë van die aanpasbare roosterkaart om sy reëlmatige eweknie na te boots.
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Rimmasch, Kathryn. "A Process-Based CALL Assessment: A Comparison of Input Processing and Program Use Behavior by Activity Type." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd2220.pdf.

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Wendt, N. Rodney. "Applications of program understanding and rule-based quality assurance to Slam II simulation programs." Thesis, University of Ottawa (Canada), 1993. http://hdl.handle.net/10393/6893.

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With the advance of time, our inventory of simulation programs has and continues to accumulate. To maximize the return on our investment of time and money into these software systems, it is advantageous for us to reuse software components as much as possible. For example, previously engineered simulation models can often be reused and exercised under a new set of experimental conditions. Before a software component can be reused, the analyst must learn and understand its functionality. This learning process is often made unnecessarily difficult due to incomplete documentation. Another contributing factor is the complexity brought about by interacting directly with the program code. Furthermore, when it comes time to make updates to the code, the potential arises for semantic and syntactic errors to work their way into the program. Knowledge-based program understanding systems with built in quality assurance can be used as an environment for simplifying the learning and the update processes, while ensuring an acceptable degree of quality has been maintained during the update process. This thesis discusses program understanding and quality assurance issues related to the Slam II programming language and discusses the architecture of E/Slam (Elucidation of Slam II programs). E/Slam is a knowledge-based program understanding system with built-in quality assurance ability.
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Shepherd, David. "Natural language program analysis combining natural language processing with program analysis to improve software maintenance tools /." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 176 p, 2007. http://proquest.umi.com/pqdweb?did=1397920371&sid=6&Fmt=2&clientId=8331&RQT=309&VName=PQD.

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Chou, Robert Shih-pei. "A program design language for COBOL." Thesis, Kansas State University, 1985. http://hdl.handle.net/2097/13200.

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Richardson, Joel E. "E a persistent systems implementation language /." Madison, Wis. : University of Wisconsin-Madison, Computer Sciences Dept, 1989. http://catalog.hathitrust.org/api/volumes/oclc/20839601.html.

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Gordon, Christopher Todd. "A visual language for ADA program unit specifications." Thesis, This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-06232009-063007/.

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Books on the topic "SLAM (Computer program language)"

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Introduction to simulation and SLAM II. 4th ed. New York: Wiley, 1995.

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Introduction to simulation and SLAM II. 3rd ed. New York: Wiley, 1986.

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O'Reilly, Jean J. SLAM II quick reference manual. West Lafayette, Ind: Pritsker & Associates, 1987.

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J, Rolston Laurie, and Floss Peter, eds. Solutions: Introduction to Simulation and SLAM II. West Lafayette, Ind: Systems Pub. Corp., 1986.

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Pritsker, A. Alan B. Simulation with Visual SLAM and AweSim. New York: Wiley, 1997.

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J, O'Reilly Jean, ed. Simulation with Visual SLAM and AweSim. 2nd ed. New York: Wiley, 1999.

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Gallis, Christos. Stochastic computer simulation of forest biomass logistics in Greece. Helsinki: Dept. of Forest Resource Management, University of Helsinki, 1997.

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Olga, Pekelny, ed. Computer language C. San Diego: Harcourt Brace Jovanovich, 1989.

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Reid, Glenn C. PostScript language program design. Reading, Mass: Addison-Wesley, 1988.

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C: How to program. 6th ed. Upper Saddle River, N.J: Pearson Prentice Hall, 2010.

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Book chapters on the topic "SLAM (Computer program language)"

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Weik, Martin H. "language program." In Computer Science and Communications Dictionary, 871. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_9931.

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Weik, Martin H. "program design language." In Computer Science and Communications Dictionary, 1347. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_14835.

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Craven, Paul Vincent. "What Is a Computer Language?" In Program Arcade Games, 33–40. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-1790-0_3.

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Volpano, Dennis, and Geoffrey Smith. "Language Issues in Mobile Program Security." In Lecture Notes in Computer Science, 25–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-68671-1_3.

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Harf, Mait, Kristiina Kindel, Vahur Kotkas, Peep Küngas, and Enn Tyugu. "Automated Program Synthesis for Java Programming Language." In Lecture Notes in Computer Science, 157–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45575-2_17.

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Roșu, Grigore. "From Rewriting Logic, to Programming Language Semantics, to Program Verification." In Lecture Notes in Computer Science, 598–616. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23165-5_28.

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Kobayashi, Naoki. "Higher-Order Program Verification and Language-Based Security." In Advances in Computer Science - ASIAN 2009. Information Security and Privacy, 17–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10622-4_2.

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Fargo, W. Scott, and W. David Woodson. "Potential Use of an Engineering-Based Computer Simulation Language (SLAM) for Modeling Insect Systems." In Estimation and Analysis of Insect Populations, 247–55. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-3664-1_16.

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Sridhar, S. "An implementation of OBJ2: An object-oriented language for abstract program specification." In Lecture Notes in Computer Science, 81–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/3-540-17179-7_5.

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Dimock, Allyn, Ian Westmacott, Robert Muller, Franklyn Turbak, J. B. Wells, and Jeffrey Considine. "Program Representation Size in an Intermediate Language with Intersection and Union Types." In Lecture Notes in Computer Science, 27–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45332-6_2.

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Conference papers on the topic "SLAM (Computer program language)"

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Steux, Bruno, and Oussama El Hamzaoui. "tinySLAM: A SLAM algorithm in less than 200 lines C-language program." In Vision (ICARCV 2010). IEEE, 2010. http://dx.doi.org/10.1109/icarcv.2010.5707402.

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Zhong-shuai, Bai, and Chen Xue-bo. "Two-Dimensional temperature prediction model of slab of reheating furnace based on C++ programme language." In 2013 3rd International Conference on Computer Science and Network Technology (ICCSNT). IEEE, 2013. http://dx.doi.org/10.1109/iccsnt.2013.6967338.

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Yang, Xiaoli, Rong Ge, and Charles Tseng. "Visualizing genetic recombination with interactive computer program." In 2010 International Conference on Audio, Language and Image Processing (ICALIP). IEEE, 2010. http://dx.doi.org/10.1109/icalip.2010.5685128.

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Kim, Sung-Hun, Jin-Tak Choi, and Kil-Hong Joo. "Development of Cyber Sign Language Interpreting App Program for Deaf." In Next Generation Computer and Information Technology 2017. Science & Engineering Research Support soCiety, 2017. http://dx.doi.org/10.14257/astl.2017.145.03.

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Ling, Xiang, Guoqing Wu, and Bo Huang. "Comparing program to requirement and design using language acceptance." In 2012 2nd International Conference on Computer Science and Network Technology (ICCSNT). IEEE, 2012. http://dx.doi.org/10.1109/iccsnt.2012.6525961.

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Qin, Yi, and Guonian Wang. "A computer-aided Chinese pronunciation training program for English-speaking learners." In 2014 International Conference on Asian Language Processing (IALP). IEEE, 2014. http://dx.doi.org/10.1109/ialp.2014.6973499.

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Menotti, Ricardo, Joao M. P. Cardoso, Marcio M. Fernandes, and Eduardo Marques. "LALP: A Novel Language to Program Custom FPGA-Based Architectures." In 2009 21st International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD). IEEE, 2009. http://dx.doi.org/10.1109/sbac-pad.2009.23.

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Dovhopolova, Hanna. "COMPUTER PROGRAM AS A METHOD OF DEVELOPING STUDENTS’ FOREIGN LANGUAGE COMMUNICATION SKILLS." In THEORETICAL AND EMPIRICAL SCIENTIFIC RESEARCH: CONCEPT AND TRENDS. European Scientific Platform, 2020. http://dx.doi.org/10.36074/24.07.2020.v3.02.

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Jin, Yuqiang, Yuliang Chen, Zijian Lin, and Junwei Lei. "Research on PID control and Simulation with M Language of Matlab Program." In 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016). Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/icence-16.2016.98.

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Yu-ping Yang, Li-yan Zhang, Chun-ying Wu, and Lie Cao. "Teaching method and practice about the course of program language design in college." In 2010 2nd International Conference on Education Technology and Computer (ICETC). IEEE, 2010. http://dx.doi.org/10.1109/icetc.2010.5529385.

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