Estimating good discrete partitions from observed data: symbolic false nearest neighbors

A symbolic analysis of observed time series data requires making a discrete partition of a continuous state space containing observations of the dynamics. A particular kind of partition, called ``generating'', preserves all dynamical information of a deterministic map in the symbolic representation, but such partitions are not obvious beyond one dimension, and existing methods to find them require significant knowledge of the dynamical evolution operator or the spectrum of unstable periodic orbits. We introduce a statistic and algorithm to refine empirical partitions for symbolic state reconstruction. This method optimizes an essential property of a generating partition: avoiding topological degeneracies. It requires only the observed time series and is sensible even in the presence of noise when no truly generating partition is possible. Because of its resemblance to a geometrical statistic frequently used for reconstructing valid time-delay embeddings, we call the algorithm ``symbolic false nearest neighbors''

Development of a frit 202 analytic standard for the Defense Waste Processing Facility

During the qualification of Frit 202 samples for the `DWPF Cold Runs`, the need for a reliable chemical frit standard became apparent. A standard was prepared by obtaining a quantity of Frit 202 and grinding into a fine powder. This material was homogenized as one slurry material volume, spray dried to prevent segregation, and hydraulically pressed into discs. These discs were fired and packaged into eleven sub-lots containing approximately 2,000 discs per sub-lot. A number of samples were obtained and analyzed by two analytic laboratories. The chemical analyses were carefully reviewed and evaluated by several statistical means. While there were several statistically significant variations between the sub-lots, it is believed that those variations are partially caused by the variability of the analytic method. These discs should provide a reliable standard for future chemical analyses of DWPF Frits similar in comparison to Frit 202. It is recommended that these discs be used as a standard material included with the representative frit sample to the independent chemical analysis laboratory, and the order of use of these standards be from sub-lot eleven to sub-lot four. It is further recommended that the NIST standard material (93a) be employed along with the 202 standard until confidence in the new standard is gained. The NIST standard should also be used when initial use of a new sub-lot is begun. this procedure should continue to the end of the DWPF program or such time as the chemical composition of the frit is extensively modified

Social presence and dishonesty in retail

Self-service checkouts (SCOs) in retail can benefit consumers and retailers, providing control and autonomy to shoppers independent from staff, together with reduced queuing times. Recent research indicates that the absence of staff may provide the opportunity for consumers to behave dishonestly, consistent with a perceived lack of social presence. This study examined whether a social presence in the form of various instantiations of embodied, visual, humanlike SCO interface agents had an effect on opportunistic behaviour. Using a simulated SCO scenario, participants experienced various dilemmas in which they could financially benefit themselves undeservedly. We hypothesised that a humanlike social presence integrated within the checkout screen would receive more attention and result in fewer instances of dishonesty compared to a less humanlike agent. This was partially supported by the results. The findings contribute to the theoretical framework in social presence research. We concluded that companies adopting self-service technology may consider the implementation of social presence in technology applications to support ethical consumer behaviour, but that more research is required to explore the mixed findings in the current study.<br/

The medical student

The Medical Student was published from 1888-1921 by the students of Boston University School of Medicine

Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models

Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions