The martensitic transformation is one of the most researched topics in the materials science during the 20th century. The second half of this century was mainly remembered by the development of several theories related with the kinetics of phase transformation, the mechanisms involved in the nucleation phenomenon, and the way as the crystallographic change is produced. In this paper are described the fundamental concepts that are defined in the crystallographic framework of the martensitic transformation. The study is focused on the application of the most outstanding crystallographic models: the Bain; the Wechsler, Lieberman & Read; and the Bowles & Mackenzie. The topic is presented based upon the particular features of the martensitic transformation, such as its non-diffusional character, type of interface between parent (austenite) and product (martensite) phases, the formation of substructural defects, and the shape change; all of these features are mathematically described by equations aimed to predict how the transformation will take place rather than to explain the actual movement of the atoms within the structure. This mathematical development is known as the Phenomenological Theory of Martensite Crystallography (PTMC).

The modeling of a process or a plant is vital for the design of its control system, since it allows predicting its dynamic and behavior under different circumstances, inputs, disturbances and noise. The main objective of this work is to identify which model is best for a permanent magnet brushless DC specific motor. For this, the mathematical model of a DC motor brushless PW16D, manufactured by Golden Motor, is presented and compared with its black box model; both are derived from experimental data. These data, the average applied voltage and the angular velocity, are acquired by a data acquisition card and imported to the computer. The constants of the mathematical model are estimated by a curve fitting algorithm based on non-linear least squares and pattern search using computational tool. To estimate the mathematical model constants by non-linear least square and search pattern, a goodness of fit of 84.88% and 80.48% respectively was obtained. The goodness of fit obtained by the black box model was 87.72%. The mathematical model presented slightly lower goodness of fit, but allowed to analyze the behavior of variables of interest such as the power consumption and the torque applied to the motor. Because of this, it is concluded that the mathematical model obtained by experimental data of the brushless motor PW16D, is better than its black box model.

Segmentation is one of the most important stages in iris recognition systems. In this paper, image preprocessing algorithms are applied in order to evaluate their impact on successful iris segmentation. The preprocessing algorithms are based on histogram adjustment, Gaussian filters and suppression of specular reflections in human eye images. The segmentation method introduced by Masek is applied on 199 images acquired under unconstrained conditions, belonging to the CASIA-irisV3 database, before and after applying the preprocessing algorithms. Then, the impact of image preprocessing algorithms on the percentage of successful iris segmentation is evaluated by means of a visual inspection of images in order to determine if circumferences of iris and pupil were detected correctly. An increase from 59% to 73% in percentage of successful iris segmentation is obtained with an algorithm that combine elimination of specular reflections, followed by the implementation of a Gaussian filter having a 5x5 kernel. The results highlight the importance of a preprocessing stage as a previous step in order to improve the performance during the edge detection and iris segmentation processes.

Programming by demonstration is a technique where, contrary to detailed programming, the robot learns from one or several demonstrations of the execution of the task by a human or another robot. A technique which allows a humanoid robot, take a tool to the head of a screw, following a similar trajectory than demonstrated trajectory by a human being, is presented. The technique also allows variations in location and orientation in the screw head. This is achieved thanks to the use of machine vision techniques and probabilistic models estimated from the demonstrated trajectories. Image processing consists of color space segmentation, and interest point’s selection in the screw head to calculate its position and orientation. The required trajectory in the presence of variations is generated using parameterized Gaussian mixture models in the task. With the above, the new required trajectories are generated in accordance to the variations. The system operation is presented through the illustration of the new trajectories, and pictures of the robot following these trajectories. Despite some limitations of the robotic platform used, acceptable results were achieved.

In this paper we describe a methodology for occupancy measure on beaches based on digital image processing techniques. This metric constitute a measure of interest for quantification of factors relates to the quality of user experience and is an import indicator in integrated management field. The proposed method has two main components: the preprocessing and occupancy density estimation. In the preprocessing stage a color correction approach is applied in order to minimize the illumination variance effects over the objects in the scene. Subsequently, the estimation begins delimiting the information regarding the environment using a mask or reference image. Gray-level gradient analysis is applied to the resulted image after the mask appliance. The results show a 2.6% margin of error that suggests the measure is an occupancy measure indicative. The obtained error is related to the auto occlusion identification and processing.

The article describes two important issues, the first is the process to design, implement and validate a mechanical dryer of oregano, using propane gas as fuel, and the second is the cost of the process of dehydrated, taking into account the cost of electric energy consumption by the fan and the cost of propane gas consumption by the heat exchanger. To achieve this, it was necessary review the state of the art and the study of the raw material (oregano), were established as premises of design the necessary technical specifications and the variables involved in the process, using conceptual methods and simulation to ensure that it complies with the ISO standard 7925:1999, which defines the requirements for the marketing of dried oregano and processed. Emphasis was made on the percentage of moisture that is 10%, the moisture of the product was found by the azeotropic distillation method, subsequently was validated the functionality and efficiency, comparing the results from an experimental design, then it was obtained the drying curve of oregano with the prototype of drying and it was checked if it meets ISO 7925:1999 standard and the NTC 4423 standard in order to obtain a final product dehydrated with the percentage of humidity appropriate

This work shows the use of rice husk in the removal of cationic dye methylene blue on continuous system. A factorial design 23 with center points and random distribution was implemented to evaluate the correlation of the experimental factors in the adsorption process. The considered variables were pH, particle size, salt presence, flow rate, dye initial concentration, and bed depth. The samples were analyzed in defined time intervals. The amount of removed dye was quantified by UV spectroscopy - Visible. Adams-Bohart, Thomas and BDST (Bed-depht/service time analysis) models were used to predict the breakthrough curves using non-linear regression and establish the characteristic parameters of the process. It was found that the transference of dye toward the adsorbent is favored by a basic pH, a small particle size, low flow rate and dye concentration, and high bed depth. The design of experiments established that the initial dye concentration and the bed depth were the most significant factors. Regarding the models, the Thomas provided the best fit to describe the breakthrough curves in experimental conditions and Adams-Bohart was found suitable for dynamic behavior limited to the initial part. Finally, BDST model exhibited a good correlation and allowed to establish that bed depth is a determinant factor for scaling process.