Relevant bibliographies by topics / Machine Interaction

Contents

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

Academic literature on the topic 'Machine Interaction'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Machine Interaction"

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Prepin, Ken, and Arnaud Revel. "Human–machine interaction as a model of machine–machine interaction: how to make machines interact as humans do." Advanced Robotics 21, no. 15 (2007): 1709–23. http://dx.doi.org/10.1163/156855307782506192.

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Spillard, Samuel, Christopher J. Turner, and Konstantinos Meichanetzidis. "Machine learning entanglement freedom." International Journal of Quantum Information 16, no. 08 (2018): 1840002. http://dx.doi.org/10.1142/s0219749918400026.

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Quantum many-body systems realize many different phases of matter characterized by their exotic emergent phenomena. While some simple versions of these properties can occur in systems of free fermions, their occurrence generally implies that the physics is dictated by an interacting Hamiltonian. The interaction distance has been successfully used to quantify the effect of interactions in a variety of states of matter via the entanglement spectrum [C. J. Turner, K. Meichanetzidis, Z. Papic and J. K. Pachos, Nat. Commun. 8 (2017) 14926, Phys. Rev. B 97 (2018) 125104]. The computation of the inte
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Beyls, Peter. "Intimate machine interaction." Visual Computer 2, no. 3 (1986): 152–58. http://dx.doi.org/10.1007/bf01900325.

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Hong, Fuxing, Dongbo Huang, and Ge Chen. "Interaction-Aware Factorization Machines for Recommender Systems." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 3804–11. http://dx.doi.org/10.1609/aaai.v33i01.33013804.

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Factorization Machine (FM) is a widely used supervised learning approach by effectively modeling of feature interactions. Despite the successful application of FM and its many deep learning variants, treating every feature interaction fairly may degrade the performance. For example, the interactions of a useless feature may introduce noises; the importance of a feature may also differ when interacting with different features. In this work, we propose a novel model named Interaction-aware Factorization Machine (IFM) by introducing Interaction-Aware Mechanism (IAM), which comprises the feature a
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Liu, Conghui. "Human-Machine Trust Interaction." International Journal of Dependable and Trustworthy Information Systems 1, no. 4 (2010): 61–74. http://dx.doi.org/10.4018/jdtis.2010100104.

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Improving user’s trust appropriately could help in designing an intelligent system and make it work effectively, especially with the fast growth of Web-base technology. This chapter introduces the solutions of improving user’s trust in human-machine interaction (HMI), especially for electronic commerce (e-commerce). The author firstly reviews the concept of trust and the main factors that affects the appropriateness of user’s trust in human-machine interaction, such as the properties of machine systems, the properties of human, and context. On the basis of these, the author further discusses t
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Coe, J. P. "Machine Learning Configuration Interaction." Journal of Chemical Theory and Computation 14, no. 11 (2018): 5739–49. http://dx.doi.org/10.1021/acs.jctc.8b00849.

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Haqqu, Rizca, and Salwa Nur Rohmah. "Interaction Process Between Humans and ChatGPT in the Context of Interpersonal Communication." Jurnal Ilmiah LISKI (Lingkar Studi Komunikasi) 10, no. 1 (2024): 23. http://dx.doi.org/10.25124/liski.v10i1.7216.

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This study examines human interaction with artificial intelligence technology, focusing on the implementation of ChatGPT, a chatbot developed by OpenAI. Through the Human-Machine Communication (HMC) approach, the research describes human-like attributes in ChatGPT, exploring emotional responses and utility in educational, professional, and personal contexts. Qualitative research methods with triangulation techniques were used for a holistic understanding, involving interviews, observations, and document analysis. The results indicate that ChatGPT can provide adaptive responses, adjusting langu
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Hoc, Jean-Michel. "From human – machine interaction to human – machine cooperation." Ergonomics 43, no. 7 (2000): 833–43. http://dx.doi.org/10.1080/001401300409044.

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Zhu, Chaoyang. "Hidden Markov Model Deep Learning Architecture for Virtual Reality Assessment to Compute Human–Machine Interaction-Based Optimization Model." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 7 (2023): 01–13. http://dx.doi.org/10.17762/ijritcc.v11i7.7736.

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Virtual Reality (VR) is a technology that immerses users in a simulated, computer-generated environment. It creates a sense of presence, allowing individuals to interact with and experience virtual worlds. Human-Machine Interaction (HMI) refers to the communication and interaction between humans and machines. Optimization plays a crucial role in Virtual Reality (VR) and Human-Machine Interaction (HMI) to enhance the overall user experience and system performance. This paper proposed an architecture of the Hidden Markov Model with Grey Relational Analysis (GRA) integrated with Salp Swarm Algori
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Lindvall, Martin, Jesper Molin, and Jonas Löwgren. "From machine learning to machine teaching." Interactions 25, no. 6 (2018): 52–57. http://dx.doi.org/10.1145/3282860.

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Dissertations / Theses on the topic "Machine Interaction"

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Tarpin-Bernard, Franck. "INTERACTION HOMME-MACHINE ADAPTATIVE." Habilitation à diriger des recherches, INSA de Lyon, 2006. http://tel.archives-ouvertes.fr/tel-00164110.

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Mes travaux se situent à la frontière des champs disciplinaires que sont l'Interaction Homme-Machine d'une part et le génie logiciel d'autre part. L'objectif général est de fournir des modèles, méthodes et outils pour construire et implémenter à moindre coût des applications interactives adaptatives et/ou facilement adaptables à divers contextes d'utilisation dans le respect d'une démarche qualité. En effet, la variabilité des dispositifs d'interaction, des utilisateurs eux-mêmes et de l'environnement dans lequel s'effectuent les interactions impose aujourd'hui de supporter divers niveaux d'ad
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Barker, Leon. "Gestures in machine interaction." Thesis, University of the Arts London, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.650303.

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Revathi, Palaniappan Natchammai. "Forest Machine Track-Soil Interaction." Thesis, KTH, Maskinkonstruktion (Inst.), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-142428.

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I många västeuropeiska länder har metoden för skogsavverkning ändrats från användning av motorsåg till ett mekaniserat skogsavverkningssystem känt som kortvirkesmetoden. Denna metod är baserad på en tvåmaskinslösning – en skördare som fäller, grenar och sågar träden enlig fördefinierade längder, och en skotare som transporterar stockarna till en lastplats för vidare transport till en bearbetningsanläggning. För att utveckla skogsmaskiner som är skonsammare för marken behövs en djupare förståelse av interaktionen mellan terrängen och dragfordonet. Huvudfokus i detta projekt ligger på bandgående
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Gouvrit, Montaño Florence. "Empathy and Human-Machine Interaction." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1313442553.

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MANURI, FEDERICO. "Visualization and Human-Machine Interaction." Doctoral thesis, Politecnico di Torino, 2017. http://hdl.handle.net/11583/2673784.

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The digital age offers a lot of challenges in the eld of visualization. Visual imagery has been effectively used to communicate messages through the ages, to express both abstract and concrete ideas. Today, visualization has ever-expanding applications in science, engineering, education, medicine, entertainment and many other areas. Different areas of research contribute to the innovation in the eld of interactive visualization, such as data science, visual technology, Internet of things and many more. Among them, two areas of renowned importance are Augmented Reality and Visual Analytics.
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Vo, Dong-Bach. "Conception et évaluation de nouvelles techniques d'interaction dans le contexte de la télévision interactive." Thesis, Paris, ENST, 2013. http://www.theses.fr/2013ENST0053/document.

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La télévision n’a cessé de se populariser et d’évoluer en proposant de nouveaux services. Ces services de plus en plus interactifs rendent les téléspectateurs plus engagés dans l’activité télévisuelle. Contrairement à l’usage d’un ordinateur, ils interagissent sur un écran distant avec une télécommande et des applications depuis leur canapé peu propice à l’usage d’un clavier et d’une souris. Ce dispositif et les techniques d’interaction actuelles qui lui sont associées peinent à répondre correctement à leurs attentes. Afin de répondre à cette problématique, les travaux de cette thèse explorent
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Westerberg, Simon. "Semi-Automating Forestry Machines : Motion Planning, System Integration, and Human-Machine Interaction." Doctoral thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-89067.

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The process of forest harvesting is highly mechanized in most industrialized countries, with felling and processing of trees performed by technologically advanced forestry machines. However, the maneuvering of the vehicles through the forest as well as the control of the on-board hydraulic boom crane is currently performed through continuous manual operation. This complicates the introduction of further incremental productivity improvements to the machines, as the operator becomes a bottleneck in the process. A suggested solution strategy is to enhance the production capacity by increasing the
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Cronin, Anna Elizabeth. "THE INTERACTION BETWEEN FUNCTION AND MACHINE PREFERENCE IN SLOT MACHINE GAMBLERS." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/theses/1538.

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Gambling is a popular pastime in the United States, and it is important that we understand the class of behaviors in a behavior analytic context. The relationship between the function and preference of gambling behavior remains yet to be explored. The purpose of these two studies is to examine this relationship. Participants were asked to play a set of four computerized slot machines. Each slot machine was tied to a separated function-based outcome which they could win. In study 1, 80% of participants had a distinct preference for a single outcome. In study 2, the participants were also admini
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Huot, Stéphane. "'Designeering Interaction': un chaînon manquant dans l'évolution de l'Interaction Homme-Machine." Habilitation à diriger des recherches, Université Paris Sud - Paris XI, 2013. http://tel.archives-ouvertes.fr/tel-00823763.

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Human Computer Interaction (HCI) is a fascinating research field because of its multidisciplinary nature, combining such diverse research domains as design, human factors and computer science as well as a variety of methods including empirical and theoretical research. HCI is also fascinating because it is still young and so much is left to discover, invent and understand. The evolution of computers, and more generally of interactive systems, is not frozen, and so are the ways in which we interact with them. From desktop computers, to mobile devices, to large displays or multi-surface environm
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Vo, Dong-Bach. "Conception et évaluation de nouvelles techniques d'interaction dans le contexte de la télévision interactive." Electronic Thesis or Diss., Paris, ENST, 2013. http://www.theses.fr/2013ENST0053.

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La télévision n’a cessé de se populariser et d’évoluer en proposant de nouveaux services. Ces services de plus en plus interactifs rendent les téléspectateurs plus engagés dans l’activité télévisuelle. Contrairement à l’usage d’un ordinateur, ils interagissent sur un écran distant avec une télécommande et des applications depuis leur canapé peu propice à l’usage d’un clavier et d’une souris. Ce dispositif et les techniques d’interaction actuelles qui lui sont associées peinent à répondre correctement à leurs attentes. Afin de répondre à cette problématique, les travaux de cette thèse explorent
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Books on the topic "Machine Interaction"

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Lalanne, Denis, and Jürg Kohlas, eds. Human Machine Interaction. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00437-7.

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Kraiss, Karl-Friedrich, ed. Advanced Man-Machine Interaction. Springer-Verlag, 2006. http://dx.doi.org/10.1007/3-540-30619-6.

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Gao, Shuo, Shuo Yan, Hang Zhao, and Arokia Nathan. Touch-Based Human-Machine Interaction. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68948-3.

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Biele, Cezary, Janusz Kacprzyk, Jan W. Owsiński, Andrzej Romanowski, and Marcin Sikorski, eds. Digital Interaction and Machine Intelligence. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74728-2.

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Biele, Cezary, Janusz Kacprzyk, Wiesław Kopeć, Jan W. Owsiński, Andrzej Romanowski, and Marcin Sikorski, eds. Digital Interaction and Machine Intelligence. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11432-8.

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Renals, Steve, Samy Bengio, and Jonathan G. Fiscus, eds. Machine Learning for Multimodal Interaction. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11965152.

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Popescu-Belis, Andrei, Steve Renals, and Hervé Bourlard, eds. Machine Learning for Multimodal Interaction. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-78155-4.

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Bengio, Samy, and Hervé Bourlard, eds. Machine Learning for Multimodal Interaction. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b105752.

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Popescu-Belis, Andrei, and Rainer Stiefelhagen, eds. Machine Learning for Multimodal Interaction. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-85853-9.

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Renals, Steve, and Samy Bengio, eds. Machine Learning for Multimodal Interaction. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11677482.

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Book chapters on the topic "Machine Interaction"

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Maybury, M. T. "Conversational Multimedia Interaction." In Machine Conversations. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4757-5687-6_5.

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Medenica, Zeljko. "Human Machine Interaction." In Wireless Networks. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94785-3_3.

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Kaindl, Hermann. "Human-Machine Interaction." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25629-6_66.

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Goldena, Nancy Jasmine. "Overview of Human-Computer Interaction." In Machine Intelligence. Auerbach Publications, 2023. http://dx.doi.org/10.1201/9781003424550-2.

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Cacciabue, Pietro Carlo. "Modelling Machine and Interaction." In Modelling and Simulation of Human Behaviour in System Control. Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-1567-0_4.

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Assayag, Gerard, George Bloch, Arshia Cont, and Shlomo Dubnov. "Interaction with Machine Improvisation." In The Structure of Style. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12337-5_10.

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Zelinsky, Alexander. "Visual Human-Machine Interaction." In Advanced Topics in Artificial Intelligence. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-46695-9_37.

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Biswas, Pradipta. "User Interaction." In Inclusive Human Machine Interaction for India. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06500-7_3.

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Marnik, Joanna. "Hand Shape Recognition for Human-Computer Interaction." In Man-Machine Interactions. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00563-3_9.

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Mohammad, Yasser, and Toyoaki Nishida. "Modelling Interaction Dynamics during Face-to-Face Interactions." In Modeling Machine Emotions for Realizing Intelligence. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12604-8_4.

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Conference papers on the topic "Machine Interaction"

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Yu, Feng, Zhaocheng Liu, Qiang Liu, Haoli Zhang, Shu Wu, and Liang Wang. "Deep Interaction Machine." In CIKM '20: The 29th ACM International Conference on Information and Knowledge Management. ACM, 2020. http://dx.doi.org/10.1145/3340531.3412077.

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Fahlquist, Karin, Johannes Karlsson, Haibo Li, et al. "Human animal machine interaction." In the international conference. ACM Press, 2010. http://dx.doi.org/10.1145/1873951.1874201.

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Al-Fedaghi, Sabah. "Informational human-machine interaction." In 2008 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, 2008. http://dx.doi.org/10.1109/icsmc.2008.4811308.

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Dwivedi, Utkarsh. "Introducing Children to Machine Learning Through Machine Teaching." In IDC '21: Interaction Design and Children. ACM, 2021. http://dx.doi.org/10.1145/3459990.3463394.

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Zhou, Zhongyi. "Exploiting and Guiding User Interaction in Interactive Machine Teaching." In UIST '22: The 35th Annual ACM Symposium on User Interface Software and Technology. ACM, 2022. http://dx.doi.org/10.1145/3526114.3558529.

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Yu, Tianzhe, Giuliano Persico, Metin Tekkalmaz, Karsten Meisberger, Hannes Raddatz, and Matthias Riedl. "IT Security for Collaborative Machines and Human-Machine Interaction." In 2021 IEEE 26th International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE, 2021. http://dx.doi.org/10.1109/etfa45728.2021.9613609.

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de Guzman, Gonzalo C., Emmanuelle Tognoli, and J. A. Scott Kelso. "Machine-induced coordination behavior in human-machine interaction." In 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2009. http://dx.doi.org/10.1109/robio.2009.5420699.

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Mackie, Ian. "The geometry of interaction machine." In the 22nd ACM SIGPLAN-SIGACT symposium. ACM Press, 1995. http://dx.doi.org/10.1145/199448.199483.

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Shier, W. A., and S. N. Yanushkevich. "Biometrics in human-machine interaction." In 2015 International Conference on Information and Digital Technologies (IDT). IEEE, 2015. http://dx.doi.org/10.1109/dt.2015.7222989.

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"Human, Computer and Machine Interaction." In 2020 IEEE 18th International Conference on Industrial Informatics (INDIN). IEEE, 2020. http://dx.doi.org/10.1109/indin45582.2020.9442200.

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Reports on the topic "Machine Interaction"

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Bass, Len, and Joelle Coutaz. Human-Machine Interaction Considerations for Interactive Software. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada206574.

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Murray, Steven A. Human-Machine Interaction With Multiple Autonomous Sensors. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada422501.

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Smith, L. The Use of Man-Machine Interaction in Data-Fitting Problems. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1453868.

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Martinovsky, Bilyana, and David Traum. The Error Is the Clue: Breakdown In Human-Machine Interaction. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada459168.

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Fang, Chen. Unsettled Issues in Vehicle Autonomy, Artificial Intelligence, and Human-Machine Interaction. SAE International, 2021. http://dx.doi.org/10.4271/epr2021010.

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Artificial intelligence (AI)-based solutions are slowly making their way into our daily lives, integrating with our processes to enhance our lifestyles. This is major a technological component regarding the development of autonomous vehicles (AVs). However, as of today, no existing, consumer ready AV design has reached SAE Level 5 automation or fully integrates with the driver. Unsettled Issues in Vehicle Autonomy, AI and Human-Machine Interaction discusses vital issues related to AV interface design, diving into speech interaction, emotion detection and regulation, and driver trust. For each
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Mohan, Arvind, Courtney Shelley, Jacob Riglin, John Bernardin, and Sara Del Valle. Machine Intelligent Survival Models of Patient – Ventilation Interaction for COVID-19. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1645040.

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Mygal, Galyna, Olga Protasenko, and Natalia Kobrina. Research of human-machine interaction on the example of the “operator-UAV” system. Peeref, 2023. http://dx.doi.org/10.54985/peeref.2304p6788671.

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Razdan, Rahul. Unsettled Topics Concerning Human and Autonomous Vehicle Interaction. SAE International, 2020. http://dx.doi.org/10.4271/epr2020025.

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This report examines the current interaction points between humans and autonomous systems, with a particular focus on advanced driver assistance systems (ADAS), the requirements for human-machine interfaces as imposed by human perception, and finally, the progress being made to close the gap. Autonomous technology has the potential to benefit personal transportation, last-mile delivery, logistics, and many other mobility applications enormously. In many of these applications, the mobility infrastructure is a shared resource in which all the players must cooperate. In fact, the driving task has
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Martinez, Kimberly D., and Gaojian Huang. Exploring the Effects of Meaningful Tactile Display on Perception and Preference in Automated Vehicles. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2164.

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There is an existing issue in human-machine interaction, such that drivers of semi-autonomous vehicles are still required to take over control of the vehicle during system limitations. A possible solution may lie in tactile displays, which can present status, direction, and position information while avoiding sensory (e.g., visual and auditory) channels overload to reliably help drivers make timely decisions and execute actions to successfully take over. However, limited work has investigated the effects of meaningful tactile signals on takeover performance. This study synthesizes literature i
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Bruun, Laura, Marta Bo, and Netta Goussac. Compliance with International Humanitarian Law in the Development and Use of Autonomous Weapon Systems: What does IHL Permit, Prohibit and Require? Stockholm International Peace Research Institute, 2023. http://dx.doi.org/10.55163/dfxr3984.

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It is undisputed that the development and use of autonomous weapon systems (AWS) must comply with international humanitarian law (IHL). However, how IHL rules should be interpreted and applied in the context of AWS remains, in some respects, unclear or disputed. With a particular focus on human–machine interaction, this report aims to facilitate a deeper understanding of this issue. Informed by an in-person expert workshop that SIPRI convened in November 2022 and contributions to the international policy discussion on AWS, the report maps areas of common ground and identifies aspects that warr
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