Young children's (Homo sapiens) understanding of knowledge formation in themselves and others.

Three- and 4-yr-old children were tested for comprehension of knowledge formation. In Exp 1, 34 Ss watched as a surprise was hidden under 1 of 4 obscured cups. The experimenter then pointed to the cup. All children searched under the correct cup, but no 3-yr-olds (in contrast to most 4-yr-olds) could explain how they knew where to look. Ss then discriminated between simultaneous pointing by 2 adults, one who had hidden a surprise and one who had left the room before the surprise was hidden. Most 4-yr-olds (but no 3-yr-olds) showed clear discrimination between the adults. In Exp 2, 16 Ss were tested with procedures designed to make the source of their own knowledge more obvious, but this had no effect on performance. It is concluded that studies using very similar procedures with chimpanzees and rhesus macaques were measuring an ability (or inability) to understand how knowledge states form. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Diagnostics of eccentricities and bar/end-ring connector breakages in polyphase induction motors through a combination of time-series data mining and time-stepping coupled FE-state-space techniques

This paper develops the foundations of a technique for detection and categorization of dynamic/static eccentricities and bar/end-ring connector breakages in squirrel-cage induction motors that is not based on the traditional Fourier transform frequency-domain spectral analysis concepts. Hence, this approach can distinguish between the "fault signatures" of each of the following faults: eccentricities, broken bars, and broken end-ring connectors in such induction motors. Furthermore, the techniques presented here can extensively and economically predict and characterize faults from the induction machine adjustable-speed drive design data without the need to have had actual fault data from field experience. This is done through the development of dual-track studies of fault simulations and, hence, simulated fault signature data. These studies are performed using our proven time-stepping coupled finite-element-state-space method to generate fault case performance data, which contain phase current waveforms and time-domain torque profiles. Then, from this data, the fault cases are classified by their inherent characteristics, so-called "signatures" or "fingerprints." These fault signatures are extracted or "mined" here from the fault case data using our novel time-series data mining technique. The dual track of generating fault data and mining fault signatures was tested here on dynamic and static eccentricities of 10% and 30% of air-gap height as well as cases of one, three, six, and nine broken bars and three, six, and nine broken end-ring connectors. These cases were studied for proof of principle in a 208 V 60 Hz four-pole 1.2 hp squirrel-cage three-phase induction motor. The paper presents faulty and healthy performance characteristics and their corresponding so-called phase space diagnoses that show distinct fault signatures of each of the above-mentioned motor faults.     

Reconstructing the evolution of mind.

Since Darwin, the idea of intellectual continuity has gripped comparative psychology. Psychological evolution has been viewed as the accumulation of gradual changes over time, resulting in an unbroken chain of mental capacities throughout the diversity of life. Some researchers have even maintained that no fundamental psychological differences exist among species. An alternative model argues that a rather profound new psychology related to mental state attribution may have evolved recently in the primate order. The author explores recent experimental research from chimpanzees, rhesus monkeys, and children that is consistent with this 2nd model of psychological evolution. Drawing on the fields of developmental, comparative, and social psychology, as well as evolutionary and developmental biology, the author outlines a research agenda aimed at reconstructing the evolution of metacognition. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A new temporal pattern identification method for characterization and prediction of complex time series events

A new method for analyzing time series data is introduced in this paper. Inspired by data mining, the new method employs time-delayed embedding and identifies temporal patterns in the resulting phase spaces. An optimization method is applied to search the phase spaces for optimal heterogeneous temporal pattern clusters that reveal hidden temporal patterns, which are characteristic and predictive of time series events. The fundamental concepts and framework of the method are explained in detail. The method is then applied to the characterization and prediction, with a high degree of accuracy, of the release of metal droplets from a welder. The results of the method are compared to those from a Time Delay Neural Network and the C4.5 decision tree algorithm.     

Evaluation of water treatment sludges toxicity using the Daphnia bioassay

Alum and ferric chloride sludges from two water treatment plants (WTPs) were analyzed regarding their physicochemical characteristics and toxicity to Daphnia similis. Experiments were carried out in the dry and rainy seasons. Acute and chronic toxicity was measured using survival and reproduction as measurement endpoints. No acute toxicity of the sludge was observed in 48 h exposure. Ferric chloride sludge caused chronic toxicity, demonstrated by low fecundity and some mortality, while alum sludge caused chronic toxicity characterized by low fecundity. Some sludge characteristics varied between samplings, including turbidity, solids contents, N, P and metal (Al and Fe) concentrations. These variables and the increase of chemical oxygen demand (COD) were identified as the main cause of degradation of the receiving waters. However, no relationship was observed between these variables and degree of toxicity. It is apparent from these results that water treatment sludges may be toxic and therefore may impair receiving waters. Alum sludge was less toxic than ferric chloride sludge.     

Factors influencing young chimpanzees' (Pan troglodytes) recognition of attention.

By 2? years of age, human infants appear to understand how others are connected to the external world through the mental state of attention and also appear to understand the specific role that the eyes play in deploying this attention. Previous research with chimpanzees suggests that, although they track the gaze of others, they may simultaneously be unaware of the underlying state of attention behind gaze. In a series of 3 experiments, the investigators systematically explored how the presence of eyes, direct eye contact, and head orientation and movement affected young chimpanzees' choice of 2 experimenters from whom to request food. The results indicate that young chimpanzees may be selectively attracted to other organisms making direct eye contact with them or engaged in postures or movements that indicate attention, even though they may not appreciate the underlying mentalistic significance of these behaviors. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Failure to find self-recognition in Asian elephants (Elephas maximus) in contrast to their use of mirror cues to discover hidden food.

Only humans, chimpanzees, and orangutans have demonstrated that they recognize their reflections in mirrors. Other mammals (including over a dozen species of monkeys) have failed to show signs of self-recognition. Recent investigations have attempted to discover if the absence of self-recognition is related to a general inability to process mirrored information. This article describes the failure to find self-recognition in two adult Asian elephants (Elephas maximus) along with their spontaneous use of mirrored information to locate otherwise hidden food. Ss responded appropriately on Trial 1 to novel placements of food items, but continued to respond to their images as if confronted by another elephant. Results are discussed in the context of the relationship (or lack thereof) between different types of mirror-mediated behavior and self-recognition. It is concluded that possession of mirror-mediated abilities is not a sufficient condition for the development of self-recognition. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Development of young children's understanding that the recent past is causally bound to the present.

The results of 6 studies (involving 304 children) suggested that 4- and 5-year olds, but not 3-year olds, understand that very recent past events determine the present. In Studies 1–3, 3- and 4-year old children were introduced to 2 empty hiding locations. With children's backs to these locations, a camera recorded an experimenter secretly hiding a puppet in one of them. Children viewed the videotape of what had just happened, along with another tape that depicted identical events with a different child and with the puppet hidden in the other location. Only 4-year olds were subsequently able to locate the puppet, even though 3-year olds remembered the contents of the tapes and understood the equivalence between the video events and the real world. In Study 4, similar effects were obtained when a verbal analog of the test was presented to 3–5 year olds. Studies 5 and 6 showed that when children observed 2 events in which they had just participated, only 5-year olds understood that the most recent events were relevant. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Time series classification using Gaussian mixture models of reconstructed phase spaces

A new signal classification approach is presented that is based upon modeling the dynamics of a system as they are captured in a reconstructed phase space. The modeling is done using full covariance Gaussian mixture models of time domain signatures, in contrast with current and previous work in signal classification that is typically focused on either linear systems analysis using frequency content or simple nonlinear machine learning models such as artificial neural networks. The proposed approach has strong theoretical foundations based on dynamical systems and topological theorems, resulting in a signal reconstruction, which is asymptotically guaranteed to be a complete representation of the underlying system, given properly chosen parameters. The algorithm automatically calculates these parameters to form appropriate reconstructed phase spaces, requiring only the number of mixtures, the signals, and their class labels as input. Three separate data sets are used for validation, including motor current simulations, electrocardiogram recordings, and speech waveforms. The results show that the proposed method is robust across these diverse domains, significantly outperforming the time delay neural network used as a baseline.     

Diagnostics of bar and end-ring connector breakage faults inpolyphase induction motors through a novel dual track of time-seriesdata mining and time-stepping coupled FE-state space modeling

This paper develops the fundamental foundations of a technique for detection of faults in induction motors that is not based on the traditional Fourier transform frequency domain approach. The technique can extensively and economically characterize and predict faults from the induction machine adjustable speed drive design data. This is done through the development of dual-track proof-of-principle studies of fault simulation and identification. These studies are performed using our proven time stepping coupled finite element-state space method to generate fault case data. Then, the fault cases are classified by their inherent characteristics, so-called "signatures" or "fingerprints." These fault signatures are extracted or mined here from the fault case data using our novel time series data mining technique. The dual-track of generating fault data and mining fault signatures was tested here on three, six, and nine broken bar and broken end-ring connectors in a 208-volt, 60-Hz, 4-pole, 1.2-hp, squirrel cage 3-phase induction motor