Academic literature on the topic 'Mobius search'
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Journal articles on the topic "Mobius search"
PRAVEEN. P, PRAVEEN P. "MSPEUX – Mobile Search Personalization by Enhanced User Experience." International Journal of Scientific Research 3, no. 5 (June 1, 2012): 237–39. http://dx.doi.org/10.15373/22778179/may2014/71.
Full textSchwartz, Stephan Andrew. "The Discovery of an American Brig: Fieldwork Involving Applied Remote Viewing Including a Comparison with Electronic Remote Sensing." Journal of Scientific Exploration 34, no. 1 (March 23, 2020): 62–92. http://dx.doi.org/10.31275/20201481.
Full textHaider, Syed Waqar, Guijun Zhuang, Hammad bin Azam Hashmi, and Shahid Ali. "Chronotypes’ Task-Technology Fit for Search and Purchase in Omnichannel Context." Mobile Information Systems 2019 (March 25, 2019): 1–9. http://dx.doi.org/10.1155/2019/8968264.
Full textShimamura, Jun. "Mobile Visual Search." Journal of the Institute of Image Information and Television Engineers 68, no. 3 (2014): 233–34. http://dx.doi.org/10.3169/itej.68.233.
Full textGirod, Bernd, Vijay Chandrasekhar, David Chen, Ngai-Man Cheung, Radek Grzeszczuk, Yuriy Reznik, Gabriel Takacs, Sam Tsai, and Ramakrishna Vedantham. "Mobile Visual Search." IEEE Signal Processing Magazine 28, no. 4 (July 2011): 61–76. http://dx.doi.org/10.1109/msp.2011.940881.
Full textXiong, Zhuangzhi, Tao Xu, Yugang Dai, and Liang Chen. "Mobile Search Development Research." Journal of Physics: Conference Series 1087 (September 2018): 032021. http://dx.doi.org/10.1088/1742-6596/1087/3/032021.
Full textPaulson, L. D. "Search technology goes mobile." Computer 38, no. 8 (2005): 19–22. http://dx.doi.org/10.1109/mc.2005.270.
Full textRoto, Virpi. "Search on mobile phones." Journal of the American Society for Information Science and Technology 57, no. 6 (2006): 834–37. http://dx.doi.org/10.1002/asi.20303.
Full textPark, So-Yeon. "Analysis of Mobile Search Functions of Korean Search Portals." Journal of the Korean Society for information Management 29, no. 1 (March 30, 2012): 175–90. http://dx.doi.org/10.3743/kosim.2012.29.1.175.
Full textN., Angel. "Hybrid Genetic Gravitational Search Algorithm for Energy Efficient Trust Node Identification in Mobile Adhoc Networks." Journal of Advanced Research in Dynamical and Control Systems 12, SP3 (February 28, 2020): 74–86. http://dx.doi.org/10.5373/jardcs/v12sp3/20201240.
Full textDissertations / Theses on the topic "Mobius search"
Katsilieris, Fotios. "Search and secure using mobile robots." Thesis, KTH, Reglerteknik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-105718.
Full textAkbas, Mehmet. "Personal information search on mobile devices." Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion-image.exe/07Sep%5FAkbas.pdf.
Full textThesis Advisor(s): Singh, Gurminder ; Otani, Thomas. "September 2007." Description based on title screen as viewed on October 22, 2007. Includes bibliographical references (p. 83-87). Also available in print.
Litter, Jansen J. "Mobile robot for search and rescue." Ohio : Ohio University, 2004. http://www.ohiolink.edu/etd/view.cgi?ohiou1176921842.
Full textMao, K. "Multi-objective search-based mobile testing." Thesis, University College London (University of London), 2017. http://discovery.ucl.ac.uk/1553273/.
Full textClaesson, Jennifer, and Henrik Gedda. "Google Ads: Understanding millennials' search behavior on mobile devices." Thesis, Linnéuniversitetet, Institutionen för marknadsföring (MF), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-75731.
Full textÖfverman, Jakob. "Information Presentation in Search Engines on Mobile Devices." Thesis, Linnaeus University, School of Computer Science, Physics and Mathematics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-7945.
Full textThis thesis discusses the possibilities to visualise the presentation layer of a search engine on a mobile device in an alternative way. Previous work in the area has shown that the use of text-based-lists can be problematic when accessed on a device with a limited display. In the scope of the thesis and in order to tackle the current problems when displaying the results a literature review was carried out. The findings of the review formed the basis for a requirement definition on which a mock-up was developed. The mock-up was then evaluated and tested during a usability test where a number of users got to experience the alternative presentation layer that uses a visualisation technique called tree- map. The results from the test show that the mock-up could be seen as a alternative to the current presentation of results. The mock-up also shows that a future implementation could also include the use of categories and sorting of information in order to provide content with a meaning.
Amoako-Frimpong, Samuel. "Search Methods for Mobile Manipulator Performance Measurement." Thesis, Marquette University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10841175.
Full textMobile manipulators are a potential solution to the increasing need for additional flexibility and mobility in industrial robotics applications. However, they tend to lack the accuracy and precision achieved by fixed manipulators, especially in scenarios where both the manipulator and the autonomous vehicle move simultaneously. This thesis analyzes the problem of dynamically evaluating the positioning error of mobile manipulators. In particular, it investigates the use of Bayesian methods to predict the position of the end-effector in the presence of uncertainty propagated from the mobile platform. Simulations and real-world experiments are carried out to test the proposed method against a deterministic approach. These experiments are carried out on two mobile manipulators—a proof-of-concept research platform and an industrial mobile manipulator—using ROS and Gazebo. The precision of the mobile manipulator is evaluated through its ability to intercept retroreflective markers using a photoelectric sensor attached to the end-effector. Compared to the deterministic search approach, we observed improved interception capability with comparable search times, thereby enabling the effective performance measurement of the mobile manipulator.
Wu, Hanwei. "Object Ranking for Mobile 3D Visual Search." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-175146.
Full textVelazquez, Elio. "Mobile agents in distributed search, a comparative study." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ57761.pdf.
Full textChen, Yu-Han Tiffany. "Interactive object recognition and search over mobile video." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/111876.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 123-131).
Cameras of good quality are now available on handheld and wearable mobile devices. The high resolution of these cameras coupled with pervasive wireless connectivity and advanced computer vision algorithms makes it feasible to develop new ways to interact with mobile video. Two important examples are interactive object recognition and search-by-content. Interactive recognition continuously locates objects in a video stream, recognizes them, and labels them with information associated with the objects in the user's view. Example use cases include an augmented shopping application that recognizes products or brands to inform customers about the items they buy and a driver assistance application that recognizes vehicles and signs to improve driver safety. Interactive search-by-content allows users to discover videos using textual queries (e.g., "child dog play"). Instead of requiring broadcasters to manually annotate videos with meta-data tags, our search system uses vision algorithms to automatically produce textual tags. These two services must be highly interactive because users expect timely feedback for their interactions and changes in content. However, achieving high interactivity without sacrificing accuracy or efficiency is challenging. The required computer vision algorithms use computationally intensive deep neural networks and must run at a frame rate of 30 frames per second. Recognizing an object scales with the size of the corpus of objects, and is infeasible on a mobile device. Off-loading recognition operations to servers introduces network and processing delay; when this delay is higher than a frame-time, it degrades recognition accuracy. This dissertation presents two systems that study the trade-off between accuracy and efficiency for interactive recognition and search, and demonstrate how to achieve both goals. Glimpse enables interactive object recognition for camera-equipped mobile devices. Because the algorithms for object recognition entail significant computation, Glimpse runs them on servers across the network. To "hide" latency, Glimpse uses an active cache of video frames on the device and performs tracking on a subset of frames to correct the stale results obtained from the processing pipeline. Our results show that Glimpse achieves a precision of 90% for face recognition, which improves over a scheme performing server-side recognition without using an active cache by 2.8 x. For fast moving objects such as road signs, Glimpse achieves precision up to 80%; without using the active cache, interactive recognition is non-functional (1.9% precision). Panorama enables search on live video streams. It introduces three new mechanisms: (1) an intelligent frame selector that reduces the number of frames on which expensive recognition must be run, (2) a distributed scheduler that uses feedback from the vision algorithms to dynamically determine the order in which streams must be processed, and (3) a search-ranking method that uses visual features to improve search relevance. Our experimental results show that incorporating visual features doubles search relevance from 45% to 90%. To achieve 90% search accuracy, with current pricing from Amazon Web Services, Panorama incurs 24x lower cost than a scheme that recognizes every frame.
by Yu-Han Tiffany Chen.
Ph. D.
Books on the topic "Mobius search"
Wu, Dan, and Shaobo Liang. Mobile Search Behaviors. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-02315-6.
Full textK, Kokula Krishna Hari, ed. Optimized Mobile Search Engine Using Click-Through Data: ICIEMS 2014. India: Association of Scientists, Developers and Faculties, 2014.
Find full textTara, Calishain, ed. Spidering hacks. Beijing: O'Reilly, 2004.
Find full textKuboviak, Jim. Legal and procedural application of mobile videotaping to criminal interdiction patrol. Jacksonville, Fla: Institute of Police Technology and Management, University of North Florida, 1997.
Find full textThe Google phone pocket guide. Berkeley, CA: Peachpit Press, 2009.
Find full textWilson, Stephen. Mobile Search and Local Search Marketing - Small Business Survival Guide. Lulu Press, Inc., 2010.
Find full textMurphy, Robin R., and Ronald C. Arkin. Disaster Robotics. MIT Press, 2014.
Find full textMurphy, Robin R. Disaster Robotics. MIT Press, 2014.
Find full textDisaster Robotics. MIT Press, 2014.
Find full textMurphy, Robin R. Disaster Robotics. MIT Press, 2014.
Find full textBook chapters on the topic "Mobius search"
Norrie, Moira C. "Desktop, Tabletop or Mobile?" In Search Computing, 46–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19668-3_5.
Full textWu, Dan, and Shaobo Liang. "Discussion and Conclusions." In Mobile Search Behaviors, 137–43. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-02315-6_5.
Full textWu, Dan, and Shaobo Liang. "Context-based Mobile Search Behaviors." In Mobile Search Behaviors, 31–77. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-02315-6_2.
Full textWu, Dan, and Shaobo Liang. "Information Search in Mobile Context." In Mobile Search Behaviors, 1–30. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-02315-6_1.
Full textWu, Dan, and Shaobo Liang. "Mobile Search Behavior Across Different Devices." In Mobile Search Behaviors, 103–35. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-02315-6_4.
Full textWu, Dan, and Shaobo Liang. "Mobile Search Behaviors and APP Usage." In Mobile Search Behaviors, 79–102. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-02315-6_3.
Full textIlarri, Sergio. "Mobile Resource Search." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_80696-2.
Full textIlarri, Sergio. "Mobile Resource Search." In Encyclopedia of Database Systems, 2277–82. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_80696.
Full textAral, Atakan, Ilker Zafer Akin, and Marco Brambilla. "Mobile Multi-domain Search over Structured Web Data." In Search Computing, 98–110. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34213-4_7.
Full textKose, Erdal. "Indexed Search." In Artificial Intelligence and Mobile Services – AIMS 2019, 84–100. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-23367-9_7.
Full textConference papers on the topic "Mobius search"
Weiss, Scott. "Mobile search." In the 9th international conference. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1377999.1378044.
Full textTiago, Pedro, Niko Kotilainen, Mikko Vapa, Heikki Kokkinen, and Jukka K. Nurminen. "Mobile Search - Social Network Search Using Mobile Devices." In 2008 5th IEEE Consumer Communications and Networking Conference. IEEE, 2008. http://dx.doi.org/10.1109/ccnc08.2007.268.
Full textTiago, Pedro, Niko Kotilainen, and Mikko Vapa. "Mobile Search - Social Network Search Using Mobile Devices Demonstration." In 2008 5th IEEE Consumer Communications and Networking Conference. IEEE, 2008. http://dx.doi.org/10.1109/ccnc08.2007.290.
Full textMichel, Maximilian, Zoran Despotovic, Wolfgang Kellerer, Qing Wei, Jorg Widmer, Norihiro Ishikawa, Takeshi Kato, and Tomoyuki Osano. "Poster: P2P search routing concepts for mobile object tracking." In 2007 Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services (MobiQuitous). IEEE, 2007. http://dx.doi.org/10.1109/mobiq.2007.4450991.
Full textErol, Berna, Jiebo Luo, Shih-Fu Chang, Minoru Etoh, Hsiao-Wuen Hon, Qian Lin, and Vidya Setlur. "Mobile media search." In the seventeen ACM international conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1631272.1631447.
Full textErol, Berna, Jordan Cohen, Minoru Etoh, Hsiao-Wuen Hon, Jiebo Luo, and Johan Schalkwyk. "Mobile media search." In ICASSP 2009 - 2009 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2009. http://dx.doi.org/10.1109/icassp.2009.4960729.
Full textGao, Wen. "Mobile Visual Search." In MobiHoc'15: The Sixteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2746285.2767183.
Full textMalhan, Rishi, and Satyandra K. Gupta. "Finding Optimal Sequence of Mobile Manipulator Placements for Automated Coverage Planning of Large Complex Parts." In ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/detc2022-90105.
Full textChen, Ning, Steven C. H. Hoi, Shaohua Li, and Xiaokui Xiao. "Mobile App Tagging." In WSDM 2016: Ninth ACM International Conference on Web Search and Data Mining. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2835776.2835812.
Full textZeng, Zhen, Adrian Röfer, and Odest Chadwicke Jenkins. "Semantic Linking Maps for Active Visual Object Search (Extended Abstract)." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/667.
Full textReports on the topic "Mobius search"
Tkachuk, Viktoriia, Serhiy Semerikov, Yuliia Yechkalo, Svitlana Khotskina, and Vladimir Soloviev. Selection of Mobile ICT for Learning Informatics of Future Professionals in Engineering Pedagogy. [б. в.], October 2020. http://dx.doi.org/10.31812/123456789/4127.
Full textCrass, David, Ichiro Suzuki, and Masafumi Yamashita. Searching for a Mobile Intruder in a Corridor - The Open Edge Variant of the Polygon Search Problem. Fort Belvoir, VA: Defense Technical Information Center, January 1994. http://dx.doi.org/10.21236/ada283918.
Full textAkua Anyidoho, Nana, Max Gallien, Mike Rogan, and Vanessa van den Boogaard. Mobile Money Taxation and Informal Workers: Evidence from Ghana’s E-Levy. Institute of Development Studies, September 2022. http://dx.doi.org/10.19088/ictd.2022.012.
Full textSadeghsalehi, Hamidreza, Parinaz Onikzeh, Afshin Heidari, Aida Kazemi, Parisa Najjariasl, Kamran Dalvandi, and Hadi Zamanian. Application of smartphone apps in assessment after spine surgeries: a systematic review protocol. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, October 2021. http://dx.doi.org/10.37766/inplasy2021.10.0054.
Full textMader, Philip, Maren Duvendack, Adrienne Lees, Aurelie Larquemin, and Keir Macdonald. Enablers, Barriers and Impacts of Digital Financial Services: Insights from an Evidence Gap Map and Implications for Taxation. Institute of Development Studies, June 2022. http://dx.doi.org/10.19088/ictd.2022.008.
Full textCantor, Amy, Heidi D. Nelson, Miranda Pappas, Chandler Atchison, Brigit Hatch, Nathalie Huguet, Brittny Flynn, and Marian McDonagh. Effectiveness of Telehealth for Women’s Preventive Services. Agency for Healthcare Research and Quality (AHRQ), June 2022. http://dx.doi.org/10.23970/ahrqepccer256.
Full textMcEntee, Alice, Sonia Hines, Joshua Trigg, Kate Fairweather, Ashleigh Guillaumier, Jane Fischer, Billie Bonevski, James A. Smith, Carlene Wilson, and Jacqueline Bowden. Tobacco cessation in CALD communities. The Sax Institute, June 2022. http://dx.doi.org/10.57022/sneg4189.
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