IMU Auto-Calibration Based on Quaternion Kalman Filter to Identify Movements of Dairy Cows.

This work is focused on developing a self-calibration algorithm for an orientation estimation of cattle movements based on a quaternion Kalman filter. The accelerometer signals in the earth's frame provide more information to confirm that the cow is performing a jump to mount another cow. To obtain the measurements in the earth's frame, we propose a self-calibration method based on a strapdown inertial navigation system (SINS), which does not require intervention by the user once deployed in the field. The self-calibration algorithm uses a quaternion-based Kalman filter to predict the angular orientation with bias correction, and update it based on the measurements of accelerometers and magnetometers. The paper also depicts an alternate update to adjust the inclination using only the accelerometer measurements. We conducted experiments to compare the accuracy of the orientation estimation when the body moves similarly to cow mount movements. The comparison is between the proposed self-calibration algorithm with the IvenSense MPU9250 and Bosch BNO055 and the quaternion attitude estimation provided in the BNO055. The auto-calibrating algorithm presents a mean error of 0.149 rads with a mean consumption of 308.5 mW, and the Bosch algorithm shows an average error of 0.139 rads with a mean consumption of 307.5 mW. When we executed this algorithm in an MPU9250, the average error was 0.077 rads, and the mean consumption was 277.7 mW.

The Joint Effects of Hubris, Growth Aspirations, and Entrepreneurial Phases for Innovative Behavior.

Innovation is often seen as essential for ventures to succeed. High business failure rates in entrepreneurship, however, suggest that innovations are frequently driven by entrepreneurs blinded by overconfidence. Thus, anticipating when and why entrepreneurs will be motivated to innovate is fundamental for entrepreneurial success. Using a large sample obtained from population surveys conducted in 77 countries, this study analyzes the variables that are significantly associated with innovative behaviors. The research tests a model proposing that the joint effects of hubris, growth aspirations, and an entrepreneur's level of entrepreneurial experience have a crucial impact on innovative endeavors. It finds that hubris is significantly related to entrepreneurs' growth aspirations and that ambition, in turn, is positively related to innovative behaviors. In addition, the study finds that both relationships are moderated by the level of entrepreneurial experience. These findings highlight the need to wise up amateur entrepreneurs before they embark on innovative endeavors.

Harvest Stage Recognition and Potential Fruit Damage Indicator for Berries Based on Hidden Markov Models and the Viterbi Algorithm.

This article proposes a monitoring system that allows to track transitions between different stages in the berry harvesting process (berry picking, waiting for transport, transport and arrival at the packing site) solely using information from temperature and vibration sensors located in the basket. The monitoring system assumes a characterization of the process based on hidden Markov models and uses the Viterbi algorithm to perform inferences and estimate the most likely state trajectory. The obtained state trajectory estimate is then used to compute a potential damage indicator in real time. The proposed methodology does not require information about the weight of the basket to identify each of the different stages, which makes it effective and more efficient than other alternatives available in the industry.

Image correlation method for DNA sequence alignment.

The complexity of searches and the volume of genomic data make sequence alignment one of bioinformatics most active research areas. New alignment approaches have incorporated digital signal processing techniques. Among these, correlation methods are highly sensitive. This paper proposes a novel sequence alignment method based on 2-dimensional images, where each nucleic acid base is represented as a fixed gray intensity pixel. Query and known database sequences are coded to their pixel representation and sequence alignment is handled as object recognition in a scene problem. Query and database become object and scene, respectively. An image correlation process is carried out in order to search for the best match between them. Given that this procedure can be implemented in an optical correlator, the correlation could eventually be accomplished at light speed. This paper shows an initial research stage where results were "digitally" obtained by simulating an optical correlation of DNA sequences represented as images. A total of 303 queries (variable lengths from 50 to 4500 base pairs) and 100 scenes represented by 100 x 100 images each (in total, one million base pair database) were considered for the image correlation analysis. The results showed that correlations reached very high sensitivity (99.01%), specificity (98.99%) and outperformed BLAST when mutation numbers increased. However, digital correlation processes were hundred times slower than BLAST. We are currently starting an initiative to evaluate the correlation speed process of a real experimental optical correlator. By doing this, we expect to fully exploit optical correlation light properties. As the optical correlator works jointly with the computer, digital algorithms should also be optimized. The results presented in this paper are encouraging and support the study of image correlation methods on sequence alignment.

Efecto de las estrategias de afrontamiento al estrés en los síntomas de estrés post-traumático en sobrevivientes de un terremoto. Hacia un modelo explicativo del estrés post-traumático / The effects of stress coping strategies in post-traumatic stress symptoms among earthquake survivors: an explanatory model of post-traumatic stress

Se determinó el efecto de las estrategias de afrontamiento (WOC) en los síntomas de estrés post-traumático (PTSD) ante un evento estresante común para 304 personas (Chile, terremoto 27 de febrero de 2010), mediante la aplicación del ways of coping questionnaire y de la davidson scale of trauma. Los resultados muestran 4 modelos de regresión lineal múltiple significativos que explican el total y los 3 tipos de síntomas del PTSD a partir de las WOC evitación y resolución de problemas. Sin embargo, un primer modelo integrado mediante ecuaciones estructurales no obtuvo buenos índices de ajuste. Se concluye con un modelo integrado alternativo que presenta muy buenos índices de ajuste. Finalmente se entregan explicaciones basadas en neuroimágenes y covert conditioning, además de reflexiones sobre prevención y prevalencia del PTSD.

The effect of the ways of coping (WOC) in post-traumatic stress disorder (PTSD) symptoms in a stressing event common to a sample of 304 people (Chile, earthquake february, 27 2010) was determined through the application of the ways of coping questionnaire and the davidson scale of trauma. The results show 4 significant regression multiple linear models explaining the total and the 3 types of PTSD symptoms through WOC such as avoidance and problem solution. However, a first integrated model through structural equations did not attain good fit indexes. The study has been concluded with an alternative integrated model presenting very good adjustment indexes (CMIN/DF=.058, RMSEA=.000, NFI=.999, CFI=.999 and PNFI=.100). Finally, explanations based on neuroimages and covert conditioning are provided along with reflections on the prevention and prevalence of the PTSD.