Predicting and improving the recognition of emotions

The technological world is moving towards more effective and friendly human computer interaction. A key factor of these emerging requirements is the ability of future systems to recognise human emotions, since emotional information is an important part of human-human communication and is therefore expected to be essential in natural and intelligent human-computer interaction. Extensive research has been done on emotion recognition using facial expressions, but all of these methods rely mainly on the results of some classifier based on the apparent expressions. However, the results of classifier may be badly affected by the noise including occlusions, inappropriate lighting conditions, sudden movement of head and body, talking, and other possible problems. In this paper, we propose a system using exponential moving averages and Markov chain to improve the classifier results and somewhat predict the future emotions by taking into account the current as well as previous emotions

Control charts for monitoring the mean of AR(1) data

New product development is one of the most powerful but difficult activities in business. It is also a very important factor affecting final product quality. There are many techniques available for new product development. Experimental design is now regarded as one of the most significant techniques. In this article, we will discuss how to use the technique of experimental design in developing a new product - an extrusion press. In order to provide a better understanding of this specific process, a brief description of the extrusion press is presented. To ensure the successful development of the extrusion press, customer requirements and expectations were obtained by detailed market research. The critical and non-critical factors affecting the performance of the extrusion press were identified in preliminary experiments. Through conducting single factorial experiments, the critical factorial levels were determined. The relationships between the performance indexes of the extrusion press and the four critical factors were determined on the basis of multi-factorial experiments. The mathematical models for the performance of the extrusion press were established according to a central composite rotatable design. The best combination of the four critical factors and the optimum performance indexes were determined by optimum design. The results were verified by conducting a confirmatory experiment. Finally, a number of conclusions became evident.

Control charts using minima instead of averages

Traditional control charts are commonly based on the averages of the inspected groups of observations. It turns out to be quite worthwhile to consider alternative approaches. In particular, a very good proposal is to use instead the group minimum for comparison to some suitable upper limit (and likewise the group maximum for comparison to a lower limit). The power of detection during Out-of-Control of the resulting chart is comparable to that of the standard Shewhart approach, while it offers much better protection to the effects of parameter estimation and/or nonnormality than the traditional methods

An Exact Formula for the Average Run Length to False Alarm of the Generalized Shiryaev-Roberts Procedure for Change-Point Detection under Exponential Observations

We derive analytically an exact closed-form formula for the standard minimax Average Run Length (ARL) to false alarm delivered by the Generalized Shiryaev-Roberts (GSR) change-point detection procedure devised to detect a shift in the baseline mean of a sequence of independent exponentially distributed observations. Specifically, the formula is found through direct solution of the respective integral (renewal) equation, and is a general result in that the GSR procedure's headstart is not restricted to a bounded range, nor is there a "ceiling" value for the detection threshold. Apart from the theoretical significance (in change-point detection, exact closed-form performance formulae are typically either difficult or impossible to get, especially for the GSR procedure), the obtained formula is also useful to a practitioner: in cases of practical interest, the formula is a function linear in both the detection threshold and the headstart, and, therefore, the ARL to false alarm of the GSR procedure can be easily computed.Comment: 9 pages; Accepted for publication in Proceedings of the 12-th German-Polish Workshop on Stochastic Models, Statistics and Their Application

Integrated maneuvering and life support system simulation Final report

Integrated maneuvering and life support system simulatio

Underlying Inflation and the Distribution of Price Change: Evidence from the Japanese Trimmed-Mean CPI

In this paper, we analyze the use of the trimmed-mean Consumer Price Index (trimmed CPI) as a measure of underlying inflation. We focus on empirical evidence that the cross-sectional price change distribution often but temporarily skews extremely to each side and that large but temporary variations in inflation correspond to the occurrence of the skewness. We find that the skewness of the distribution is mainly caused by idiosyncratic, temporary relative price shocks and that the components which contribute to the skewness of the distribution shift from time to time. Trimming 15 percent from each tail of the cross-sectional price change distribution systematically mitigates the fluctuation of the price index related to broad-based temporary relative price shocks. Thus, the trimmed CPI can be regarded as more appropriate for identifying underlying inflation compared with the CPI excluding fresh foods (CPI ex. fresh foods), which is generally regarded as the "core inflation index" in Japan. Distinguishing temporary price variations and underlying inflation using a measure of the skewness of the price change distribution provides central banks with increased information for evaluations of prior policies and present price developments, and for predictions of future inflation.