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Relevant bibliographies by topics / Human-computer interaction Mobile computing. Artificial intelligence

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Journal articles

Academic literature on the topic 'Human-computer interaction Mobile computing. Artificial intelligence'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Human-computer interaction Mobile computing. Artificial intelligence"

1

Ramasubbareddy, Somula, Evakattu Swetha, Ashish Kumar Luhach, and T. Aditya Sai Srinivas. "A Multi-Objective Genetic Algorithm-Based Resource Scheduling in Mobile Cloud Computing." International Journal of Cognitive Informatics and Natural Intelligence 15, no. 3 (2021): 58–73. http://dx.doi.org/10.4018/ijcini.20210701.oa5.

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Mobile cloud computing is an emerging technology in recent years. This technology reduces battery consumption and execution time by executing mobile applications in remote cloud server. The virtual machine (VM) load balancing among cloudlets in MCC improves the performance of application in terms of response time. Genetic algorithm (GA) is popular for providing optimal solution for load balancing problems. GA can perform well in both homogeneous and heterogeneous environments. In this paper, the authors consider multi-objective genetic algorithm for load balancing in MCC (MOGALMCC) environment

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2

Tanaka, Kazuo. "Advanced Computational Intelligence in Control Theory and Applications." Journal of Advanced Computational Intelligence and Intelligent Informatics 3, no. 2 (1999): 67. http://dx.doi.org/10.20965/jaciii.1999.p0067.

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We are witnessing a rapidly growing interest in the field of advanced computational intelligence, a "soft computing" technique. As Prof. Zadeh has stated, soft computing integrates fuzzy logic, neural networks, evolutionary computation, and chaos. Soft computing is the most important technology available for designing intelligent systems and control. The difficulties of fuzzy logic involve acquiring knowledge from experts and finding knowledge for unknown tasks. This is related to design problems in constructing fuzzy rules. Neural networks and genetic algorithms are attracting attention for t

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3

Kiguchi, Kazuo, Keigo Watanabe, and Toshio Fukuda. "Trajectory Planning of Mobile Robots Using DNA Computing." Journal of Advanced Computational Intelligence and Intelligent Informatics 8, no. 3 (2004): 295–301. http://dx.doi.org/10.20965/jaciii.2004.p0295.

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DNA computers are attracting increasing attention as next-generation replacements for conventional electronic computers. Computation is realized using the chemical reaction of DNA. This paper presents optimal trajectory planning for mobile robots using DNA computing. The working area of a mobile robot is divided into many sections and the shortest trajectory avoiding obstacles in the work area is calculated by DNA computing. The location of obstacles is known in advance. In DNA computing, Watson-Crick pairing is used to find this trajectory. DNA sequences representing locations of obstacles ar

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Huang, Su-Zhen, Min Wu, and Yong-Hua Xiong. "Mobile Transparent Computing to Enable Ubiquitous Operating Systems and Applications." Journal of Advanced Computational Intelligence and Intelligent Informatics 18, no. 1 (2014): 32–39. http://dx.doi.org/10.20965/jaciii.2014.p0032.

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Mobile devices have emerged as an indispensable part of our daily life, one that has resulted in an increased demand for mobile devices to be able to access the Internet and obtain a variety of network services. However, mobile devices are often constrained by limited storage, huge power consumption, and low processing capability. This paper presents a new computing mode, mobile transparent computing (MTC), which combines ubiquitous mobile networks with transparent computing, to address the above challenges and possibly to enable a new world of ubiquitous operating systems (OSes) and applicati

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Bessghaier, Narjes, Makram Soui, Christophe Kolski, and Mabrouka Chouchane. "On the Detection of Structural Aesthetic Defects of Android Mobile User Interfaces with a Metrics-based Tool." ACM Transactions on Interactive Intelligent Systems 11, no. 1 (2021): 1–27. http://dx.doi.org/10.1145/3410468.

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Smartphone users are striving for easy-to-learn and use mobile apps user interfaces. Accomplishing these qualities demands an iterative evaluation of the Mobile User Interface (MUI). Several studies stress the value of providing a MUI with a pleasing look and feel to engaging end-users. The MUI, therefore, needs to be free from all kinds of structural aesthetic defects. Such defects are indicators of poor design decisions interfering with the consistency of a MUI and making it more difficult to use. To this end, we are proposing a tool (Aesthetic Defects DEtection Tool (ADDET)) to determine th

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Agmon, Noa, Vikas Agrawal, David W. Aha, et al. "Reports of the AAAI 2011 Conference Workshops." AI Magazine 33, no. 1 (2012): 57–70. http://dx.doi.org/10.1609/aimag.v33i1.2390.

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The AAAI-11 workshop program was held Sunday and Monday, August 7–18, 2011, at the Hyatt Regency San Francisco in San Francisco, California USA. The AAAI-11 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Activity Context Representation: Techniques and Languages; Analyzing Microtext; Applied Adversarial Reasoning and Risk Modeling; Artificial Intelligence and Smarter Living: The Conquest of Complexity; AI for Data Center Management and Cloud Computing; Automated Action Planning for Autonomous Mobile Robots; Com

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7

Goksel Canbek, Nil, and Mehmet Emin Mutlu. "On the track of Artificial Intelligence: Learning with Intelligent Personal Assistants." International Journal of Human Sciences 13, no. 1 (2016): 592. http://dx.doi.org/10.14687/ijhs.v13i1.3549.

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<p>In a technology dominated world, useful and timely information can be accessed quickly via Intelligent Personal Assistants (IPAs). By the use of these assistants built into mobile operating systems, daily electronic tasks of a user can be accomplished 24/7. Such tasks like taking dictation, getting turn-by-turn directions, vocalizing email messages, reminding daily appointments, setting reminders, responding any factual questions and invoking apps can be completed by IPAs such as Apple’s <a href="http://searchconsumerization.techtarget.com/definition/Siri" target="_blank">Siri&l

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Meng, Max Q.-H., and Hong Zhang. "Perspectives of Computational Intelligence in Robotics and Automation." Journal of Advanced Computational Intelligence and Intelligent Informatics 8, no. 3 (2004): 235–36. http://dx.doi.org/10.20965/jaciii.2004.p0235.

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As people attempt to build biomimetic robots and realize automation processes through artificial intelligence, computational intelligence plays a very important role in robotics and automation. This special issue contains several important papers that address various aspects of computational intelligence in robotics and automation. While acknowledging its limited coverage, this special issue offers a range of interesting contributions such as intelligent trajectory planning for flying and land mobile robots, fuzzy decision making, control of rigid and teleoperated robots, modeling of human sen

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Jin, Lin, and Changhong Yan. "Research on Key Technologies of Massive Videos Management Under the Background of Cloud Platform." Journal of Advanced Computational Intelligence and Intelligent Informatics 23, no. 1 (2019): 72–77. http://dx.doi.org/10.20965/jaciii.2019.p0072.

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With the rapid development of mobile internet and smart city, video surveillance is popular in areas such as transportation, schools, homes, and shopping malls. It is important subject to manage the massive videos quickly and accurately. This paper tries to use Hadoop cloud platform for massive video data storage, transcoding and retrieval. The key technologies of cloud computing and Hadoop are introduced firstly in the paper. Then, we analyze the functions of video management platform, such as user management, videos storage, videos transcoding, and videos retrieval. According to the basic fu

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10

Liu, Peter Xiaoping, Max Q.-H. Meng, and Jason J. Gu. "Intelligent Scaling Control for Internet-Based Teleoperation." Journal of Advanced Computational Intelligence and Intelligent Informatics 8, no. 3 (2004): 275–83. http://dx.doi.org/10.20965/jaciii.2004.p0275.

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In this paper we present an intelligent scaling control algorithm, which is based on the hierarchical decomposition and dynamic assignment of tasks between the human operator and the on-board controller of the remote robot, for mobile robot teleoperation over the Internet. This control scheme relies on the real-time estimation of concurrent roundtrip delays in order to assign tasks between the user and the robot optimally. For this purpose, we employ a linear neural network for which most conventional learning algorithms are infeasible since their required computation is usually too intensive

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