Circular Hough Transform For Detecting And Measuring Circles of Object

This article presents a robust method for detecting and measuring the circles of industrial object like water pump pulley(WPP-44), images based on circular Hough transform. The software of the application is based on detecting and measuring the circles surrounding of that object. The objective of this application is the recognition of circular shapes in an image. This paper presents efficient implementation of Image Processing technique for measurement of dimension of the object used in Turbine system. The proposed work makes use of the Matlab software for the said work..At First an segmentation or edge detection technique is used for finding the edges in the input image, then the characteristic points of circles are determined, after this process the pattern of the circles is extracted, and then with the help of other extraction parameter of the diameter of object(WPP-44). DOI: 10.17762/ijritcc2321-8169.15023

Salience-based selection: attentional capture by distractors less salient than the target

Current accounts of attentional capture predict the most salient stimulus to be invariably selected first. However, existing salience and visual search models assume noise in the map computation or selection process. Consequently, they predict the first selection to be stochastically dependent on salience, implying that attention could even be captured first by the second most salient (instead of the most salient) stimulus in the field. Yet, capture by less salient distractors has not been reported and salience-based selection accounts claim that the distractor has to be more salient in order to capture attention. We tested this prediction using an empirical and modeling approach of the visual search distractor paradigm. For the empirical part, we manipulated salience of target and distractor parametrically and measured reaction time interference when a distractor was present compared to absent. Reaction time interference was strongly correlated with distractor salience relative to the target. Moreover, even distractors less salient than the target captured attention, as measured by reaction time interference and oculomotor capture. In the modeling part, we simulated first selection in the distractor paradigm using behavioral measures of salience and considering the time course of selection including noise. We were able to replicate the result pattern we obtained in the empirical part. We conclude that each salience value follows a specific selection time distribution and attentional capture occurs when the selection time distributions of target and distractor overlap. Hence, selection is stochastic in nature and attentional capture occurs with a certain probability depending on relative salience

Some experiments with the 3-D hough shape transform

Journal ArticleThe application of the Hough shape transform to the problem of the identification and localization of objects in 3-space is presented. The rotation-invariant Hough transform is defined which permits the determination of the geometric transformation from the model to the detected object. Given a sample of 3-D surface points, a set of special model points are derived which are used to form the model. Methods are presented for reducing the amount of computation and accumulator space requited to perform the analysis

The Neurodynamic Decision Variable in Human Multi-Alternative Perceptual Choice

The neural dynamics underpinning binary perceptual decisions and their transformation into actions are well studied, but real-world decisions typically offer more than two response alternatives. How does decision-related evidence accumulation dynamically influence multiple action representations in humans? The heightened conservatism required in multiple compared to binary choice scenarios suggests a mechanism which compensates for increased uncertainty when multiple choices are present by supressing baseline activity. Here, we tracked action representations using corticospinal excitability during four and two-choice perceptual decisions, and modelled them using a sequential sampling framework. We found that the predictions made by leaky competing accumulator models in order to accommodate multiple choices (i.e. reduced baseline activity to compensate increased uncertainty) were borne out by dynamic changes in human action representations. This suggests a direct and continuous influence of interacting evidence accumulators, each favouring a different decision alternative, on downstream corticospinal excitability during complex choice

Pattern recognition in a multi-sensor environment

Journal ArticleCurrent pattern recognition systems tend to operate on a single sensor, e.g., a camera. however. the need is now evident for pattern recognition systems which can operate in multi-sensor environments. For example, a robotics workstation may use range finders. cameras, tactile pads, etc. The Multi-sensor Kernel System (MKS) provides an efficient and coherent approach to the specification, recovery, and analysis of patterns in the data sensed by such a diverse set of sensors. We demonstrate how much a system can be used to support both feature-based object models as well as structural models. The problems solved is the localization of a three-dimensional object in 3-space. Moreover, MKS allows rapid reconfiguration of the available sensors and the high-level models

OPTIMIZATION AND CONTROL OF ARRAYS OF WAVE ENERGY CONVERTERS

Wave Energy Converter Array is a practical approach to harvest ocean wave energy. To leverage the potential of the WEC array in terms of energy extraction, it is essential to have a properly designed array configuration and control system. This thesis explores the optimal configuration of Wave Energy Converters (WECs) arrays and their optimal control. The optimization of the WEC array allows both dimensions of individual WECs as well as the array layout to varying. In the first optimization problem, cylindrical buoys are assumed in the array where their radii and drafts are optimization parameters. Genetic Algorithms are used for optimization. Three case studies are investigated of different array sizes: 3, 5, and 7 devices in the array. Two types of controls are assumed; the first is the standard impedance matching control while the second is a derivative control. The numerical test cases demonstrate that a higher q-factor is achieved when optimizing the buoys dimensions simultaneously with the array layout. In the conducted test cases, it is shown that optimizing the array layout can increase the q-factor on average by 39.21% when using optimal control, and increase it on average by a factor of 8.87% when using a derivative control. Arrays of wave energy converters (WECs) usually have large spacing between members of the array to avoid negative hydrodynamic interaction between members in the array. Errors in estimating the spacing between members may result in a significant degradation in the performance of the array in terms of the total harvested energy, due to destructive hydrodynamic interaction between members of the array. In this thesis, a hybrid design of wave energy converter arrays, that contains two types of WECs, the heaving buoys, and the floating flap-type devices, is investigated and compared against traditional WEC arrays of heaving buoys. The resulting q-factor is less sensitive to deviations in the spacing from the design layout. This hybrid array, hence, enables more WECs in the same ocean area. The two types of arrays are tested using 40 layouts that have different separation distances ranging from small to large. With the hybrid configuration, the array achieved a variance of the q-factor as low as 0.006. The traditional array has a variance of 0.024 which is four times larger. The optimization is conducted on the hybrid array with both layout and dimension as design variables. The optimal control algorithm for the WEC array is developed using the optimality condition. Devices in the array are assumed to be identical heaving buoys. The optimization objective is to maximize energy extraction at each time step. Both regular and irregular waves are used to excite the array. The unconstrained optimal control problem is solved with saturation on the control force. The solutions show that good wave estimations and sufficient accuracy of the radiation sub-system are the keys to the desired WEC array performance

Project OASIS: The Design of a Signal Detector for the Search for Extraterrestrial Intelligence

An 8 million channel spectrum analyzer (MCSA) was designed the meet to meet the needs of a SETI program. The MCSA puts out a very large data base at very high rates. The development of a device which follows the MCSA, is presented

Efficient decoding algorithms for generalized hidden Markov model gene finders

BACKGROUND: The Generalized Hidden Markov Model (GHMM) has proven a useful framework for the task of computational gene prediction in eukaryotic genomes, due to its flexibility and probabilistic underpinnings. As the focus of the gene finding community shifts toward the use of homology information to improve prediction accuracy, extensions to the basic GHMM model are being explored as possible ways to integrate this homology information into the prediction process. Particularly prominent among these extensions are those techniques which call for the simultaneous prediction of genes in two or more genomes at once, thereby increasing significantly the computational cost of prediction and highlighting the importance of speed and memory efficiency in the implementation of the underlying GHMM algorithms. Unfortunately, the task of implementing an efficient GHMM-based gene finder is already a nontrivial one, and it can be expected that this task will only grow more onerous as our models increase in complexity. RESULTS: As a first step toward addressing the implementation challenges of these next-generation systems, we describe in detail two software architectures for GHMM-based gene finders, one comprising the common array-based approach, and the other a highly optimized algorithm which requires significantly less memory while achieving virtually identical speed. We then show how both of these architectures can be accelerated by a factor of two by optimizing their content sensors. We finish with a brief illustration of the impact these optimizations have had on the feasibility of our new homology-based gene finder, TWAIN. CONCLUSIONS: In describing a number of optimizations for GHMM-based gene finders and making available two complete open-source software systems embodying these methods, it is our hope that others will be more enabled to explore promising extensions to the GHMM framework, thereby improving the state-of-the-art in gene prediction techniques