This paper introduces a user experience design project that aspires to redefine the relationship between humans and vehicles. The authors have designed the visual representation of an artificial intelligence (AI) agent, Yui. The agent is intended to elicit a sense of collaboration with the vehicle, and enable to build rapport between driver and vehicle. In the age of automated vehicles (AVs) it is critical to develop such a cooperative relationship between humans and vehicles in order for the people to more readily adopt AVs. Autonomous capability is expected to roll out in progressive phases. In the phases of partially or conditional AVs, drivers need to be engaged and alert at all time so they can quickly take back control of the vehicle. This project attempts to utilize speculative prototypes of an anthropomorphic AI agent to explore the factors necessary to engage drivers in safe collaboration with AVs.

We propose an AI-assisted design concept exploration tool, the “Character Space Construction” (“CSC”). Concept designers explore and articulate the target product aesthetics and semantics in language, which is expressed using “Design Concept Phrases” (“DCPs”), that is, compound adjective phrases, and contrasting terms that convey what are not their target design concepts. Designers often utilize this dichotomy technique to communicate the nature of their aesthetic and semantic design concepts with stakeholders, especially in an early design development phase. The CSC assists this designers' cognitive activity by constructing a “Character Space” (“CS”), which is a semantic quadrant system, in a structured manner. A CS created by designers with the assistance of the CSC enables them to discern and explain their design concepts in contrast with opposing terms. These terms in a CS are retrieved and combined in the CSC by using a knowledge graph. The CSC presents terms and phrases as lists of candidates to users from which users will choose in order to define the target design concept, which is then visualized in a CS. The participants in our experiment, who were in the “arts and design” profession, were given two conditions under which to create DCPs and explain them. One group created and explained the DCPs with the assistance of the proposed CSC, and the other did the same task without this assistance, given the freedom to use any publicly available web search tools instead. The result showed that the group assisted by the CSC indicated their tasks were supported significantly better, especially in exploration, as measured by the Creativity Support Index (CSI).

We propose the Mood Board Composer (MBC), which supports concept designers in retrieving and composing images on a 2-D concept space to communicate design concepts. The MBC allows users to iterate adaptive image retrievals intuitively. Our new contribution to the mood board tool is to adapt the query vector for the next iteration according to the user's rearrangement of images on the 2-D space. The algorithm emphasizes the meaning of the labels on the x-and y-axes by calculating the mean vector of the images on the mood board multiplied by the weights assigned to each cell of the 3 grid. The next image search is performed by obtaining the most similar words from the mean vector thus obtained and using them as a new query. In addition to the algorithm described above, we conducted the participant experiment with two other interaction algorithms to compare. The first allows users to delete unwanted images and go on to the next searches. The second utilizes the semantic labels on each image, on which users can provide negative feedback for query modification for the next searches. Although we did not observe significant differences among the three proposed algorithms, our experiment with 420 cases of mood board creation confirmed the effectiveness of adaptive iterations by the Creativity Support Index (CSI) score.

The x-ray diffraction experiments were performed on LiNbO 3 (LN) and Sr x Ba 1-x Nb 2 O 6 (SBN) crystals grown by modified Stepanov technique in bulk-profiled configuration using dies of capillary type with different cross-sections. The lattice defects were visualized by x-ray topography. The experiments show the presence in LN samples mosaic blocks drawn out along pulling direction with sizes 5-20 mm in this direction and 0.3-2.0 mm in perpendicular to growth axis. Adjacent blocks were also misoriented with respect to each other with average angles of 6 arc min. Structure distortions for c-cut of bulk-profiled LN have a character of concentric rings, those form and sizes match to the die construction. The picture of structural imperfections depends on growth conditions forming of crystal-melt interface. For profiled LN grown in high temperature gradients the phase interface was inhomogeneous: flat over die plates, concave to the capillaries. The position of rocking curve maximum depends on xray incident angle and displaces together linear scanning along LN sample surface. It indicates the presence of crystallographic plane bend of 0.6+-0.1 degree. Low thermal conductivity of SBN crystals leads to formation of convex to the crystal crystallization front what allows to eliminate such lattice defects as small angle grain boundaries and as a result to obtain crystals of high optical quality. Atomic structure of SBN (x=0.33; 0.61;0.75) was investigated. Peculiarities of distribution of Sr and Ba ions as well as Ce, Tm doping ions in lattice channels are determined.