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Journal articles on the topic 'Human computer interactio'

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Author: Grafiati

Published: 11 March 2023

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1

Zhang, Tongda, Xiao Sun, Yueting Chai, and Hamid Aghajan. "Human Computer Interaction Activity Based User Identification." International Journal of Machine Learning and Computing 4, no. 4 (2014): 354–58. http://dx.doi.org/10.7763/ijmlc.2014.v4.436.

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2

Bulling, Andreas, and Kai Kunze. "Eyewear computers for human-computer interaction." Interactions 23, no. 3 (April 26, 2016): 70–73. http://dx.doi.org/10.1145/2912886.

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3

Swartout, William, Ron Artstein, Eric Forbell, Susan Foutz, H. Chad Lane, Belinda Lange, Jacquelyn Ford Morie, Albert Skip Rizzo, and David Traum. "Virtual Humans for Learning." AI Magazine 34, no. 4 (December 15, 2013): 13–30. http://dx.doi.org/10.1609/aimag.v34i4.2487.

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Virtual humans are computer-generated characters designed to look and behave like real people. Studies have shown that virtual humans can mimic many of the social effects that one finds in human-human interactions such as creating rapport, and people respond to virtual humans in ways that are similar to how they respond to real people. We believe that virtual humans represent a new metaphor for interacting with computers, one in which working with a computer becomes much like interacting with a person and this can bring social elements to the interaction that are not easily supported with conventional interfaces. We present two systems that embody these ideas. The first, the Twins are virtual docents in the Museum of Science, Boston, designed to engage visitors and raise their awareness and knowledge of science. The second SimCoach, uses an empathetic virtual human to provide veterans and their families with information about PTSD and depression.

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Toledo, Guadalupe Toledo, J. Jesús Arellano Pimentel, Francisco Aguilar Acevedo, and Edwin Williams Molina Rodriguez. "Aprendizaje Basado en Proyectos Dentro de un Curso Universitario de Interacción Humano Computadora." RECIBE, REVISTA ELECTRÓNICA DE COMPUTACIÓN, INFORMÁTICA, BIOMÉDICA Y ELECTRÓNICA 7, no. 2 (October 31, 2018): C3–1—C3–27. http://dx.doi.org/10.32870/recibe.v7i2.101.

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Hablar de un software de calidad involucra tratar con dos disciplinas importantes, la ingeniería de software y la interacción humano computadora, esta segunda atiende el desarrollo bajo el acompañamiento de los usuarios finales, por lo que resulta atractivo integrar el aprendizaje basado en proyectos como seguimiento de un curso universitario, los cuales estarán diseñados a largo plazo resolviendo una problemática real y afín al estudiante con la intensión que éste se comprometa en proporcionar su solución, tomando como guía curricular el diseño centrado en el usuario. La determinación de los puntos de control bajo esta metodología ha permitido relacionar con éxito los conceptos de la asignatura con proyectos que ofrezcan un beneficio a la sociedad, al cierre de las actividades y productos solicitados se espera que los estudiantes puedan desarrollar artículos de divulgación.

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Modi, Nandini, and Jaiteg Singh. "Role of Eye Tracking in Human Computer Interaction." ECS Transactions 107, no. 1 (April 24, 2022): 8211–18. http://dx.doi.org/10.1149/10701.8211ecst.

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With the invention of computers arises the need of an interface for users and interacting with a computer has become a natural practice. For all the opportunities a machine can bring, it is now a limiting factor for humans and their interaction with machines. This has given rise to a significant amount of research in the area of human computer interaction to make it more intuitive, simpler, and efficient. Human interaction with computers is no longer confined to printers and keyboards. Traditional input devices give way to natural inputs like voice, gestures, and visual computing using eye tracking. This paper provides useful insights in understanding the use of eye gaze tracking technology for human-machine interaction. A case study was conducted with 15 participants to analyze eye movements on an educational website. Visual attention was measured using eye gaze fixations data and heat maps were utilized to illustrate the results.

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Gambino, Andrew, Jesse Fox, and Rabindra Ratan. "Building a Stronger CASA: Extending the Computers Are Social Actors Paradigm." Human-Machine Communication 1 (February 1, 2020): 71–86. http://dx.doi.org/10.30658/hmc.1.5.

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The computers are social actors framework (CASA), derived from the media equation, explains how people communicate with media and machines demonstrating social potential. Many studies have challenged CASA, yet it has not been revised. We argue that CASA needs to be expanded because people have changed, technologies have changed, and the way people interact with technologies has changed. We discuss the implications of these changes and propose an extension of CASA. Whereas CASA suggests humans mindlessly apply human-human social scripts to interactions with media agents, we argue that humans may develop and apply human-media social scripts to these interactions. Our extension explains previous dissonant findings and expands scholarship regarding human-machine communication, human-computer interaction, human-robot interaction, human-agent interaction, artificial intelligence, and computer-mediated communication.

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7

Cheng, Yuyang, Benjamin Fang, Kai Lu, Xingyu Wei, Yifan Wang, Michael Yang, Xingchen Zhou, and Zhenrong Zhang. "Overview of key technologies of human-computer interaction." BCP Business & Management 18 (April 13, 2022): 414–21. http://dx.doi.org/10.54691/bcpbm.v18i.579.

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In the 21st century, computers are developing faster and faster. Human-computer interaction(HCL) is defined as a multidisciplinary field of study which focuses on the interaction between humans and computer technology. The advancement of HCL makes a great contribution to nowadays’ society as human beings gradually perceive themselves in a technological world that is in a time of high-speed development.The situation of human-computer interaction is becoming more and more common, and computers have more and more intelligent factors. The latest computer technology has been applied to various disciplines, which have developed rapidly and achieved remarkable research results. In this paper, we summarizes the core technologies involved in human-computer interaction (HCI), mainly including human-computer interaction psychology, flexible screen technology, target recognition and classification, and expounds the current situation and development trend of these technologies.

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8

Ali, Miss Aliya Anam Shoukat, and Dr V. K. Shandilya. "A Review Paper on Retina Based Cursor Movement Control." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (March 31, 2022): 185–87. http://dx.doi.org/10.22214/ijraset.2022.40590.

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Abstract: In this paper a new system exists which uses human iris for computer interaction. With vast development in recent technologies, modern computing systems are becoming more flexible. Modern computers are capable of processing millions of instructions per second. In such situation, traditional input devices such as mouse or keyboard are relatively slow. This can overcome by human interaction with the computers. With the innovation and development in technologies, motion sensors are capable of capturing positions and natural movement of human body. Due to this a new way for interacting with computers is possible. Hence keeping all this in mind, we propose a system, which is untouched & fast communication system. The system would be capable of capturing eyeball movements which is responsible for Controlling the cursor. The system processes the data from the camera feed, and calibrates the parameter interfaces in accordance to the user. The system then performs computer vision related algorithms to determine the location of the use’s pupils and eyeballs so as to implement Natural eye-computer Interaction Keywords: Human Iris, Cursor Control, Electro-oculography, CAMSHIFT algorithm, Limbus Limbus Tracking, Pupile Pupil tracking.

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9

Kobayashi, Hill Hiroki. "Research in Human-Computer-Biosphere Interaction." Leonardo 48, no. 2 (April 2015): 186–87. http://dx.doi.org/10.1162/leon_a_00982.

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Currently human-computer interaction (HCI) is primarily focused on human-centric interactions. However, people experience many non-human-centric interactions every day. Interactions with nature can reinforce the importance of our relationship with nature. This paper presents the author’s vision of human-computer-biosphere interaction (HCBI) to facilitate non-human-centric interaction with the goal of moving society towards environmental sustainability.

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10

Hu, Jiayi, Qianchen Ma, Sizhou Liu, Zewei Liu, Zirui Luo, Yaxin Li, Chuanpu Liu, Kunxuan Lu, and Hanxia Li. "The Development Status and Market Analysis of Human-computer Interaction." BCP Business & Management 13 (November 16, 2021): 154–59. http://dx.doi.org/10.54691/bcpbm.v13i.79.

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Human-computer interaction is one of the main branches of computer science, which aims to study how computers, robots and other systems interact with users in a reasonable manner. In this paper, we reviewed the development history and current situation of Human-computer interaction. And, the current application of Human-computer interaction in vertical industry is introduced. Finally, we analyze the market development prospect of Human-computer interaction in the future.

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11

McNeese, Michael D. "New visions of human–computer interaction: making affect compute." International Journal of Human-Computer Studies 59, no. 1-2 (July 2003): 33–53. http://dx.doi.org/10.1016/s1071-5819(03)00059-4.

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12

de Oliveira Schultz Ascari, Rúbia Eliza, Luciano Silva, and Roberto Pereira. "Computer Vision applied to improve interaction and communication of people with motor disabilities: A systematic mapping." Technology and Disability 33, no. 1 (February 24, 2021): 11–28. http://dx.doi.org/10.3233/tad-200308.

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BACKGROUND: The use of computers as a communication tool by people with disabilities can serve as an alternative effective to promote social interactions and the more inclusive and active participation of people in society. OBJECTIVE: This paper presents a systematic mapping of the literature that provides a survey of scientific contributions where Computer Vision is applied to enable users with motor and speech impairments to access computers easily, allowing them to exert their communicative abilities. METHODS: The mapping was conducted employing searches that identified 221 potentially eligible scientific articles published between 2009 and 2019, indexed by ACM, IEEE, Science Direct, and Springer databases. RESULTS: From the retrieved papers, 33 were selected and categorized into themes of this research interest: Human-Computer Interaction, Human-Machine Interaction, Human-Robot Interaction, Recreation, and surveys. Most of the chosen studies use sets of predefined gestures, low-cost cameras, and tracking a specific body region for gestural interaction. CONCLUSION: The results offer an overview of the Computer Vision techniques used in applied research on Assistive Technology for people with motor and speech disabilities, pointing out opportunities and challenges in this research domain.

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13

Swiderska, Aleksandra, Eva G. Krumhuber, and Arvid Kappas. "Behavioral and Physiological Responses to Computers in the Ultimatum Game." International Journal of Technology and Human Interaction 15, no. 1 (January 2019): 33–45. http://dx.doi.org/10.4018/ijthi.2019010103.

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This article describes how studies in the area of decision-making suggest clear differences in behavioral responses to humans versus computers. The current objective was to investigate decision-making in an economic game played only with computer partners. In Experiment 1, participants were engaged in the ultimatum game with computer agents and regular computers while their physiological responses were recorded. In Experiment 2, an identical setup of the game was used, but the ethnicity of the computer agents was manipulated. As expected, almost all equitable monetary splits offered by the computer were accepted. The acceptance rates gradually decreased when the splits became less fair. Although the obtained behavioral pattern implied a reaction to violation of the rule of fairness by the computer in the game, no evidence was found for participants' corresponding emotional involvement. The findings contribute to the body of research on human-computer interaction and suggest that social effects of computers can be attenuated.

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Dawood, Dr Amina Atiya, and Balasem Alawi Hussain. "Machine Learning for Single and Complex 3D Head Gestures: Classification in Human-Computer Interaction." Webology 19, no. 1 (January 20, 2022): 1431–45. http://dx.doi.org/10.14704/web/v19i1/web19095.

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This paper presents a new Hidden Markov Model based approach for fast and automatic detection and classification of head movements in real time dynamic videos. The model has been developed to utilize human-computer interaction applications by using only the laptop webcam. The proposed model has the ability to predict single head and combined simultaneously in fast responses. Other models paid more attention to classify head nod and shake only, but our model contribute the role of other head movements. The model proposed here doesn’t need any user intervention or previous knowledge of its environment. In addition, there is no limitation on illumination changes and occlusions, as well as no restrictions on head movements ranges. The model achieved significant results and efficient performances when tested on unseen data. As the model accuracies were 94%, 99%, 83%, 87%, 93%, 96% for all head gestures (rest, nod, turn, shake, tilt and tilting) respectively. On the other hand, the model accuracy was 99% and 88% for combined and single cues respectively. The aim of this model is to provide a fast application to infer and predict human emotions and affective states in real time through head gestures.

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15

Al-Ma'aitah, Mohammed, Ayed Alwadain, and Aldosary Saad. "Application dependable interaction module for computer vision-based human-computer interactions." Computers & Electrical Engineering 97 (January 2022): 107553. http://dx.doi.org/10.1016/j.compeleceng.2021.107553.

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16

Nakauchi, Yasushi. "Special Issue on Human Robot Interaction." Journal of Robotics and Mechatronics 14, no. 5 (October 20, 2002): 431. http://dx.doi.org/10.20965/jrm.2002.p0431.

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Recent advances in robotics are disseminating robots into the social living environment as humanoids, pets, and caregivers. Novel human-robot interaction techniques and interfaces must be developed, however, to ensure that such robots interact as expected in daily life and work. Unlike conventional personal computers, such robots may assume a variety of configurations, such as industrial, wheel-based, ambulatory, remotely operated, autonomous, and wearable. They may also implement different communications modalities, including voice, video, haptics, and gestures. All of these aspects require that research on human-robot interaction become interdisciplinary, combining research from such fields as robotics, ergonomics, computer science and, psychology. In the field of computer science, new directions in human-computer interaction are emerging as post graphical user interfaces (GUIs). These include wearable, ubiquitous, and real-world computing. Such advances are thereby bridging the gap between robotics and computer science. The open-ended problems that potentially face include the following: What is the most desirable type of interaction between human beings and robots? What sort of technology will enable these interactions? How will human beings accept robots in their daily life and work? We are certain that readers of this special issue will be able to find many of the answers and become open to future directions concerning these problems. Any information that readers find herein will be a great pleasure to its editors.

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17

Helou, Samar, Victoria Abou-Khalil, Riccardo Iacobucci, Elie El Helou, and Ken Kiyono. "Automatic Classification of Screen Gaze and Dialogue in Doctor-Patient-Computer Interactions: Computational Ethnography Algorithm Development and Validation." Journal of Medical Internet Research 23, no. 5 (May 10, 2021): e25218. http://dx.doi.org/10.2196/25218.

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Background The study of doctor-patient-computer interactions is a key research area for examining doctor-patient relationships; however, studying these interactions is costly and obtrusive as researchers usually set up complex mechanisms or intrude on consultations to collect, then manually analyze the data. Objective We aimed to facilitate human-computer and human-human interaction research in clinics by providing a computational ethnography tool: an unobtrusive automatic classifier of screen gaze and dialogue combinations in doctor-patient-computer interactions. Methods The classifier’s input is video taken by doctors using their computers' internal camera and microphone. By estimating the key points of the doctor's face and the presence of voice activity, we estimate the type of interaction that is taking place. The classification output of each video segment is 1 of 4 interaction classes: (1) screen gaze and dialogue, wherein the doctor is gazing at the computer screen while conversing with the patient; (2) dialogue, wherein the doctor is gazing away from the computer screen while conversing with the patient; (3) screen gaze, wherein the doctor is gazing at the computer screen without conversing with the patient; and (4) other, wherein no screen gaze or dialogue are detected. We evaluated the classifier using 30 minutes of video provided by 5 doctors simulating consultations in their clinics both in semi- and fully inclusive layouts. Results The classifier achieved an overall accuracy of 0.83, a performance similar to that of a human coder. Similar to the human coder, the classifier was more accurate in fully inclusive layouts than in semi-inclusive layouts. Conclusions The proposed classifier can be used by researchers, care providers, designers, medical educators, and others who are interested in exploring and answering questions related to screen gaze and dialogue in doctor-patient-computer interactions.

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18

Jones, Steve, and Steve Marsh. "Human-computer-human interaction." ACM SIGCHI Bulletin 29, no. 3 (July 1997): 36–40. http://dx.doi.org/10.1145/264853.264872.

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19

Aiyub, Feri Fadli, and Munawir Munawir. "Kontrol Mouse Menggunakan Webcam Berdasarkan Deteksi Warna." JTIM : Jurnal Teknologi Informasi dan Multimedia 1, no. 1 (May 15, 2019): 73–77. http://dx.doi.org/10.35746/jtim.v1i1.18.

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The interaction technology in general is inseparable from the rapid development of Human-Computer Interaction technology or Human and Computer Interaction. Human and computer mouse interactions are called Virtual Mouse. Virtual mouse is designed for users to be able to interact directly with computers without using input devices such as conventional mice but using their hands as driving objects or using other media such as colors. In this research, testing is done on how to track an object that moves in order to do the mouse by using an intermediary in the form of an image processing-based webcam video that is taken in real-time using object tracking in the form of three color variables arranged based on RGB composition using the optical flow method in detecting its movement. Based on research that has been carried out as a whole the color object used as a pointer controller or mouse with the optical flow method can be detected properly in every condition.

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20

MOON, YOUNGME, and CLIFFORD NASS. "Are computers scapegoats? Attributions of responsibility in human–computer interaction." International Journal of Human-Computer Studies 49, no. 1 (July 1998): 79–94. http://dx.doi.org/10.1006/ijhc.1998.0199.

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21

Jadhav, Suvrunda, and Patil T R. "Human Computer Interaction." IJARCCE 6, no. 3 (March 30, 2017): 141–42. http://dx.doi.org/10.17148/ijarcce.2017.6329.

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22

Smithson, Steve. "Human-Computer Interaction." European Journal of Information Systems 1, no. 2 (March 1991): 143. http://dx.doi.org/10.1057/ejis.1991.23.

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23

Jacob, Robert J. K. "Human-computer interaction." ACM Computing Surveys 28, no. 1 (March 1996): 177–79. http://dx.doi.org/10.1145/234313.234387.

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24

Carver, Liz, and Murray Turoff. "Human-computer interaction." Communications of the ACM 50, no. 3 (March 2007): 33–38. http://dx.doi.org/10.1145/1226736.1226761.

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25

Ebert, Achim, Nahum D. Gershon, and Gerrit C. van der Veer. "Human-Computer Interaction." KI - Künstliche Intelligenz 26, no. 2 (March 1, 2012): 121–26. http://dx.doi.org/10.1007/s13218-012-0174-7.

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26

Grudin, Jonathan. "Human-computer interaction." Annual Review of Information Science and Technology 45, no. 1 (2011): 367–430. http://dx.doi.org/10.1002/aris.2011.1440450115.

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27

Monk, Andrew. "What's happening: computers and fun and Seventh IFIP conference on human-computer interaction." Interactions 5, no. 5 (September 1998): 7–8. http://dx.doi.org/10.1145/285213.285214.

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28

Dermawan, Ari, Sumantri Sumantri, Sudarmin Sudarmin, and Indra Ramadona Harahap. "Tinjauan Yuridis Interaksi Manusia Terhadap Digital Dalam Penegakan Hukum Di Era Revolusi Industri 4.0." Prosiding Seminar Nasional Riset Information Science (SENARIS) 1 (September 30, 2019): 1041. http://dx.doi.org/10.30645/senaris.v1i0.115.

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Human and computer interaction or human computer interaction or abbreviated as HCI is a discipline that studies the relationship between humans and computers. Human to digital interactions are increasing according to human needs that are increasingly complex. At present the world community has entered the stage of industrial revolution 4.0, and law enforcement is needed so that in the Era of the industrial revolution 4.0. get legal certainty in using digital technology or computer technology. As for the formulation of the problem is the Juridical Review of Human Interaction on Digital in Law Enforcement in the Age of Industrial Revolution 4.0, How the causes of misuse of Human Interaction Against Digital in the Age of Industrial Revolution 4.0, and How to prevent abuse of Human Interaction against Digital in the Era of Industrial Revolution . The research methodology uses normative research and library research data collection tools. Human Interaction Against Digital in Law Enforcement In the Age of Industrial Revolution 4.0 the legal foundation is needed, namely the Criminal Code and Law Number 11 of 2008 concerning Information and Electronic Transactions. Causes of Abuse of Human Interaction Against Digital in the Era of Industrial Revolution 4.0. among others are unlimited internet access. Efforts to Prevent Abuse of Human Interaction Against Digital in the Era of Industrial Revolution 4.0 can be done with the support of special institutions, both state-owned and NGOs (Non Governmental organizations).

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Zander, Thorsten O., and Laurens R. Krol. "Team PhyPA: Brain-Computer Interfacing for Everyday Human-Computer Interaction." Periodica Polytechnica Electrical Engineering and Computer Science 61, no. 2 (May 5, 2017): 209. http://dx.doi.org/10.3311/ppee.10435.

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Brain-computer interfaces can provide an input channel from humans to computers that depends only on brain activity, bypassing traditional means of communication and interaction. This input channel can be used to send explicit commands, but also to provide implicit input to the computer. As such, the computer can obtain information about its user that not only bypasses, but also goes beyond what can be communicated using traditional means. In this form, implicit input can potentially provide significant improvements to human-computer interaction. This paper describes a selection of work done by Team PhyPA (Physiological Parameters for Adaptation) at the Technische Universität Berlin to use brain-computer interfacing to enrich human-computer interaction.

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Diwan, Mr Nihal, Prof Dhiraj Kalyankar, and Dr R. R. Keole. "Review Paper on Live Eye Gaze Tracking to Control Mouse Pointer Movement." International Journal for Research in Applied Science and Engineering Technology 10, no. 8 (August 31, 2022): 411–13. http://dx.doi.org/10.22214/ijraset.2022.46149.

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Abstract: With recent advances in technology, modern computer systems are becoming more flexible. Modern computers are capable of processing millions of information per second. In such cases, traditional input devices such as a mouse or keyboard are relatively slow. In this paper we use system that can be overcome by human interaction with the computer. With innovation and development in technology, motion sensors are able to capture the position and natural movements of the human body. This has made possible a new way of communication with computers. So keeping all these in mind we propose a system which is an untouched and fast communication system. This system will be able to capture the movements of the eyeball for which it is responsible cursor control. The system processes the data in the camera feed and calibrates the parameter interface according to the user. The system then performs computer-related algorithms to determine the location of the doll's and use eyes to implement natural eye-computer interactions

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31

Hoa Tat Thang. "Computer control in human-machine interaction systems by hand movements." Journal of Military Science and Technology, CSCE5 (December 15, 2021): 42–48. http://dx.doi.org/10.54939/1859-1043.j.mst.csce5.2021.42-48.

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Computers have become popular in recent years. The forms of human-computer interaction are increasingly diverse. In many cases, controlling the computer is not only through the mouse and keyboard, but humans must control the computer through body language and representation. For some people with physical disabilities, controlling the computer through hand movements is essential to help them interact with the computer. The field of simulation also needs these interactive applications. This paper studies a solution to build a hand tracking and gesture recognition system that allows cursor movement and corresponding actions with mouse and keyboard. The research team confirms that the system works stably, accurately and can control the computer instead of a conventional mouse and keyboard through the implementation and evaluation.

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Retnoningsih, Endang, and Ari Nurul Alfian. "Human Computer Interaction Pengelolaan Open Journal Systems berbasis Interaction Framework." BINA INSANI ICT JOURNAL 7, no. 1 (June 28, 2020): 95. http://dx.doi.org/10.51211/biict.v7i1.1338.

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Abstrak: Open Journal Systems (OJS) adalah aplikasi perangkat lunak open source untuk mengelola dan menerbitkan jurnal ilmiah, untuk mendukung fungsinya tersebut Open Journal Systems (OJS) secara umum memiliki fitur yang dalam perkembangan setiap versinya mengalami perbaikan dan penyesuaian dengan kebutuhan. Proses penerbitan jurnal sangat berdampak pada proses akreditasi jurnal, oleh karena itu perlu dipahami proses bisnis alur pengiriman artikel dari author menggunakan Open Journal Systems (OJS) hingga artikel di publish. Dalam sistem diperlukan pemodelan perencanaan, desain dan penggunaan interface antara pengguna dan komputer, interaksi ini dikenal sebagai interaksi antara manusia dengan komputer (Human Computer Interaction). Framework digunakan untuk memahami interaksi sistem komputer memberikan fasilitas bahasa antara bahasa user dan bahasa sistem. Pengguna (user) dan sistem komputer (system) dapat saling berinteraksi menggunakan beberapa cara interaksi yaitu style kombinasi form fill-in dan direct manipulation. Open Journal Systems (OJS) 3.x. memiliki tampilan yang lebih ringkas, mudah dan flexible karena dibangun dengan prinsip Interaction Framework melibatkan user, input, system, output. Kata kunci: framework, HCI, jurnal, OJS, PKP Abstract: Open Journal Systems (OJS) is an open source software application to manage and publish scientific journals, to support this function Open Journal Systems (OJS) generally has features that in each version's development experience improvements and adjustments to the needs. The process of publishing a journal greatly affects the accreditation process of the journal, therefore it is necessary to understand the business process of sending articles from the author using Open Journal Systems (OJS) until the article is published. In the system required modeling planning, design and use of interfaces between users and computers, this interaction is known as the interaction between humans and computers (Human Computer Interaction). Framework is used to understand the interaction of computer systems to provide language facilities between the user's language and system language. Users (users) and computer systems (systems) can interact with each other using several modes of interaction, namely the combination style form fill-in and direct manipulation. Open Journal Systems (OJS) 3.x. has a more concise, easy and flexible appearance because it is built on the principle of Interaction Framework involving users, input, system, output. Keywords: framework, HCI, journals, OJS, PKP

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33

Caruana, Nathan, Dean Spirou, and Jon Brock. "Human agency beliefs influence behaviour during virtual social interactions." PeerJ 5 (September 20, 2017): e3819. http://dx.doi.org/10.7717/peerj.3819.

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In recent years, with the emergence of relatively inexpensive and accessible virtual reality technologies, it is now possible to deliver compelling and realistic simulations of human-to-human interaction. Neuroimaging studies have shown that, when participants believe they are interacting via a virtual interface with another human agent, they show different patterns of brain activity compared to when they know that their virtual partner is computer-controlled. The suggestion is that users adopt an “intentional stance” by attributing mental states to their virtual partner. However, it remains unclear how beliefs in the agency of a virtual partner influence participants’ behaviour and subjective experience of the interaction. We investigated this issue in the context of a cooperative “joint attention” game in which participants interacted via an eye tracker with a virtual onscreen partner, directing each other’s eye gaze to different screen locations. Half of the participants were correctly informed that their partner was controlled by a computer algorithm (“Computer” condition). The other half were misled into believing that the virtual character was controlled by a second participant in another room (“Human” condition). Those in the “Human” condition were slower to make eye contact with their partner and more likely to try and guide their partner before they had established mutual eye contact than participants in the “Computer” condition. They also responded more rapidly when their partner was guiding them, although the same effect was also found for a control condition in which they responded to an arrow cue. Results confirm the influence of human agency beliefs on behaviour in this virtual social interaction context. They further suggest that researchers and developers attempting to simulate social interactions should consider the impact of agency beliefs on user experience in other social contexts, and their effect on the achievement of the application’s goals.

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34

Murthy, G. R. S., and R. S. Jadon. "Computer Vision Based Human Computer Interaction." Journal of Artificial Intelligence 4, no. 4 (September 15, 2011): 245–56. http://dx.doi.org/10.3923/jai.2011.245.256.

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Mancini, Clara. "Animal-computer interaction." Interactions 18, no. 4 (July 2011): 69–73. http://dx.doi.org/10.1145/1978822.1978836.

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Pineda, Roger Gacula. "Where the Interaction Is Not." International Journal of Art, Culture and Design Technologies 5, no. 1 (January 2016): 1–12. http://dx.doi.org/10.4018/ijacdt.2016010101.

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The concept of interaction is foundational in technology interface design with its presuppositions being taken for granted. But the interaction metaphor has become ambiguous to the extent that its application to interface design contributes to misalignments between people's expected and actual experience with computers. This article re-examines the presuppositions governing human-computer interaction with the motivation of strengthening weaknesses in their foundational concepts. It argues for abandoning the interaction metaphor to refocus design discourse toward the mediation roles of technology interfaces. ‘Remediation', i.e. representation of one medium in another, is proposed as a conceptual model that more precisely describes the human-to-computer actions.

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Abu-Akel, Ahmad M., Ian A. Apperly, Stephen J. Wood, and Peter C. Hansen. "Re-imaging the intentional stance." Proceedings of the Royal Society B: Biological Sciences 287, no. 1925 (April 15, 2020): 20200244. http://dx.doi.org/10.1098/rspb.2020.0244.

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The commonly used paradigm to investigate Dennet's ‘intentional stance’ compares neural activation when participants compete with a human versus a computer. This paradigm confounds whether the opponent is natural or artificial and whether it is intentional or an automaton. This functional magnetic resonance imaging study is, to our knowledge, the first to investigate the intentional stance by orthogonally varying perceptions of the opponents' intentionality (responding actively or passively according to a script) and embodiment (human or a computer). The mere perception of the opponent (whether human or computer) as intentional activated the mentalizing network: the temporoparietal junction (TPJ) bilaterally, right temporal pole, anterior paracingulate cortex (aPCC) and the precuneus. Interacting with humans versus computers induced activations in a more circumscribed right lateralized subnetwork within the mentalizing network, consisting of the TPJ and the aPCC, possibly reflective of the tendency to spontaneously attribute intentionality to humans. The interaction between intentionality (active versus passive) and opponent (human versus computer) recruited the left frontal pole, possibly in response to violations of the default intentional stance towards humans and computers. Employing an orthogonal design is important to adequately capture Dennett's conception of the intentional stance as a mentalizing strategy that can apply equally well to humans and other intentional agents.

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Shaorya, Raj, Kalia Tuhin, Aggarwal Shivansh, Jaglan Sahil, Nijhawan Nikita, and Sharma Mugdha. "Human Computer Interaction using Virtual User Computer Interaction System." International Journal of Performability Engineering 18, no. 6 (2022): 396. http://dx.doi.org/10.23940/ijpe.22.06.p2.396406.

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Sumi, Kaoru. "Affective Human Computer Interaction." Journal of Robotics, Networking and Artificial Life 3, no. 2 (2016): 74. http://dx.doi.org/10.2991/jrnal.2016.3.2.2.

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Guo, Philip. "Clarifying human-computer interaction." Communications of the ACM 57, no. 2 (February 2014): 10–11. http://dx.doi.org/10.1145/2557448.

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DeFernandez, Sofia C. "Human computer interaction: introduction." XRDS: Crossroads, The ACM Magazine for Students 3, no. 3 (April 1997): 2. http://dx.doi.org/10.1145/270974.332126.

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Barnes, Julie, Rob Bryant, Daniel D. McCracken, and Susan Reiser. "Teaching human-computer interaction." ACM SIGCSE Bulletin 35, no. 1 (January 11, 2003): 125–26. http://dx.doi.org/10.1145/792548.611901.

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Manaris, Bill. "Editorial - Human-Computer Interaction." Computer Science Education 13, no. 3 (September 2003): 173–76. http://dx.doi.org/10.1076/csed.13.3.173.14948.

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Baber, Christopher, and Konrad Baumann. "Embedded human computer interaction." Applied Ergonomics 33, no. 3 (May 2002): 273–87. http://dx.doi.org/10.1016/s0003-6870(02)00013-3.

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Oulasvirta, Antti, and Stephen Brewster. "Mobile human–computer interaction." International Journal of Human-Computer Studies 66, no. 12 (December 2008): 833–37. http://dx.doi.org/10.1016/j.ijhcs.2008.10.001.

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Sumi, Kaoru. "Affective Human Computer Interaction." Proceedings of International Conference on Artificial Life and Robotics 21 (January 29, 2016): 244–48. http://dx.doi.org/10.5954/icarob.2016.is2.

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Carbonell, Noelle. "Multimodal human-computer interaction." ACM SIGCHI Bulletin 26, no. 3 (July 1994): 15–16. http://dx.doi.org/10.1145/181518.181519.

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Rehm, Matthias, Yukiko Nakano, Elisabeth André, and Toyoaki Nishida. "Enculturating human–computer interaction." AI & SOCIETY 24, no. 3 (June 23, 2009): 209–11. http://dx.doi.org/10.1007/s00146-009-0220-7.

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Lytras, Miltiadis D., Francisco Garcia-Peñalvo, and Patricia Ordóñez de Pablos. "Advanced human–computer interaction." Computers in Human Behavior 29, no. 2 (March 2013): 305–6. http://dx.doi.org/10.1016/j.chb.2012.11.018.

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Kelly, John. "The ontological status of computers or what is a computer?" AI & Society 6, no. 4 (October 1992): 305–23. http://dx.doi.org/10.1007/bf02472784.

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