Exploring the user engagement factors in computer mediated communication

User engagement can be defined as the perception of the user to qualify the experience towards certain application, which focus on the positive aspects of the interaction through Internet in the context of the desire to use it continuously and for longer time. It is fundamental concept in the design of online applications regardless of the platform, driven by the observation that successful applications are not only used but those that work. However, user engagement in the technology advancement is a paradox phenomenon, as they recognize the potentiality but reluctant to adopt or they realize its use to solve problem but prefer the other solution for longer of time. The usual ways to evaluate them can be through self-report measures, observational methods, speech analysis or web analytics. These methods represent different compensations in term of configuration, the size of object and the scale of data to be collected. For example, some study might find detail and deep analysis but they are limited in term of generalizability, while the other might found out resourceful but denies the user reasoning and the context. During this millennial, the diffusion of innovation became the acceptable theory that majority academician and practical expert use to explain the phenomenon of the reason and factor to adopt certain product. Therefore, due to the assumption of several factors such as technology advancement and paradigm shift, this study want to explore current situation in the user engagement factors, which focused to computer mediated communication

What can crowd computing do for the next generation of AI systems?

The unprecedented rise in the adoption of artificial intelligence techniques and automation in many contexts is concomitant with shortcomings of such technology with respect to robustness, interpretability, usability, and trustworthiness. Crowd computing offers a viable means to leverage human intelligence at scale for data creation, enrichment, and interpretation, demonstrating a great potential to improve the performance of AI systems and increase the adoption of AI in general. Existing research and practice has mainly focused on leveraging crowd computing for training data creation. However, this perspective is rather limiting in terms of how AI can fully benefit from crowd computing. In this vision paper, we identify opportunities in crowd computing to propel better AI technology, and argue that to make such progress, fundamental problems need to be tackled from both computation and interaction standpoints. We discuss important research questions in both these themes, with an aim to shed light on the research needed to pave a future where humans and AI can work together seamlessly, while benefiting from each other.</p

DNA-like duplexes with repetitions. III. Efficient template-guided chemical polymerization of d(TGGCCAAGCTp).

Self-association of a decanucleotide d(TGGCCAAGCTp) in an aqueous solution is shown by UV spectroscopy, CD and sedimentation analysis to yield a pseudopolymeric (concatemeric) duplex having a geometry similar to that of DNA B-type. It is demonstrated that in conditions when the concatemeric duplex is stable a water-soluble carbodiimide induces efficient polymerization of the 3'- or 5'-phosphorylated decanucleotide, and the resulting polymers d(TGGCCAAGCTp)2-10 contain only natural phosphodiester bonds. In conditions optimal for template-guided polymerization of d(TGGCCAAGCTp) the overall yield of 20-100-member polynucleotides exceeds 90%. The obtained polymeric duplexes are cleaved by restriction endonuclease Alu II, Bsu RI, and Hind III to corresponding decamers which were isolated and sequenced