EL EMPRENDEDOR ACADÉMICO Y SUS MOTIVACIONES PARA CREAR

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A New Interface Identification Technique Based on Absolute Density Gradient for Violent Flows

A New Interface Identification Technique Based on Absolute Density Gradient for Violent Flows

𝜃 = 0.97 in Fig. 5(a) and (b), which are in the range of 𝜃 proposed by Koshizuka and Oka [Koshizuka and Oka (1996)]. One can observe that the interface particles are highly over-identified with many inner particles are marked as interface ones although it is moderately relieved by decreasing the coefficient. Such over-identification was also observed by Zheng et al. [Zheng, Ma and Duan (2014)] in their dam breaking simulation. There are also several particles located on the interface but not identified by using either value of 𝜃. Other 𝜃 values are also tested and the results are shown in Fig. 6. One can find that decreasing the value helps alleviate over-identification of inner particles but more interface particles are also missed. The reasons for such inaccuracy are that the accuracy of the PND method strongly depends on the randomness of the particle distribution [Ma and Zhou (2009)]. For inner particles, coarse distribution leads to low particle number density even with a complete support domain and so over-identification happens. On the contrast, particles clustering on the interface leads to high particle number density even though the support domain of its own phase is incomplete, leading to their misidentification to inner particles. For the results obtained using the MPAM shown in Fig. 5(c), the accuracy is significantly improved. But over-identification still happens on inner particles close to the interface. Since this identification technique is based on the interface particles identified at the previous time step, error accumulation may occur after long time simulation. Fig. 5(d) shows the results obtained by the method proposed in this paper. It can be seen that almost all the interface particles are correctly identified. No inner particles are wrongly identified by the method. As indicated above, the new technique does not depend on the density ratio. To confirm this, the tests are also carried out on different density ratios of 0.1 and 0.01 in addition to the ratio of 0.9 in Fig. 5(d) by using the ADG method, and the results for the density ratios of 0.1 and 0.01are shown in Fig. 7. This figure and Fig. 5(d) show that the accurate identification is achieved in all the cases, demonstrating that results of the ADG method are independent of the density ratios.
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Least squares-based iterative identification methods for linear-in-parameters systems using the decomposition technique

Least squares-based iterative identification methods for linear-in-parameters systems using the decomposition technique

Parameter estimation and mathematical models are essential for system identification [13, 31, 33], system optimization [16, 24] and state and data filtering [14, 19, 32]. Exploring new parameter esti- mation methods is an eternal theme of system identification [5, 6] and many identification methods have been developed for linear and nonlinear systems [1, 25, 38, 40], dual-rate sampled systems [9, 11, 36] and state-delay systems [28]. Iterative methods can be used for estimating parameters and solving matrix equations [4]. The iterative identification algorithms make full use of the measured data at each iteration and thus can produce more accurate parameter estimates than the existing recursive identification algorithms [29]. For decades, many iterative methods have been applied in the parameter estimation, such as the Newton iterative method [7, 26, 41, 42], the gradient based
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Parameter Identification of Nonlinear Systems with Time delay Based on the Multi innovation Stochastic Gradient Algorithm

Parameter Identification of Nonlinear Systems with Time delay Based on the Multi innovation Stochastic Gradient Algorithm

Abstract This paper considers the parameter identification problem of block-oriented Hammerstein nonlinear systems with time-delay. Firstly, we adopt the data filtering technique to transform the identification model so that all the parameters will be separated in the resulting identification model which has no redundant parameters. Secondly, a multi-innovation stochastic gradient algorithm is used to estimate the system parameters. The proposed method has high computational efficiency and good accuracy. Simulation results are presented to demonstrate the effectiveness of the proposed algorithm.
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IMAGE COMPRESSION TECHNIQUE USING GRADIENT BASED EDGE DETECTION AND F- TRANSFORM

IMAGE COMPRESSION TECHNIQUE USING GRADIENT BASED EDGE DETECTION AND F- TRANSFORM

There are numerous techniques proposed in recurrence space by utilizing change strategies i.e. DCT, DWT and so on however they actualized on entire image as similarly and does not consider the substance varieties in the image. To consider variable rate of compression in same image, edge identification situated strategy has been proposed in which edge pixels are discovered utilizing angle of the area and after that diverse compression rates has been chosen for the non-covering pieces of the image to be compacted. Where there are more edges in the piece, calculation choses less compression and where less no. of edges is, calculation chooses high compression rate. F-change has been utilized for compression and decompression purposes. Analyses comes about shows high an incentive in PSNR, SSIM quality measurements after decompression the images and less estimations of MSE, RMSE and SAD parameters as this is a prerequisite of a decent compression decompression procedure
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Image  Retrieval Using Shape Measures and BTC

Image Retrieval Using Shape Measures and BTC

The images are very rich in the content like color, texture, shape information present in them. Retrieving images based on color similarity is achieved by computing color histogram for each image that identifies the proportion of pixels within an image holding specific values (that humans express as colors). Color searches will usually involve comparing color histograms, though this is not the only technique in practice. Texture measures look for visual patterns in images and how they are spatially defined. The identification of specific textures in an image is achieved primarily by modeling texture as a two-dimensional gray level variation[3]. The relative brightness of pairs of pixels is computed such that degree of contrast, regularity, coarseness and directionality may be estimated. Shape does not refer to the shape of an image but to the shape of a particular region that is being sought out. Shapes will often be determined first applying segmentation or edge detection to an image. Other methods use shape filters to identify given shapes of an image. In some case accurate shape detection will require human intervention because methods like segmentation are very difficult to completely automate. Here the paper discuss shape extraction using edge detection masks like Sobel, Roberts, Prewitt and Canny gradient operators[4].Some other CBIR systems with their disadvantages are QBIC – Query by Image Content reqires long indexing time[17].The problem associated with Virage are weights attached to each image. VisualSEEk considers spatial relationships between objects.Global features like mean color, color histogram can give many false positives. Disadvantage of MARS are weight updating, Modification of distance function. Disadvantage of Pic-Hunter is Probability asoociated with each image[18,19].
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Vibration spectroscopic technique for species identification based on lipid characteristics

Vibration spectroscopic technique for species identification based on lipid characteristics

that functional groups have strong and narrow absorption bands in the MIR region but very broad and weak absorbance in the NIR region. Therefore, NIR spectroscopy is more commonly used for quantitative analysis while MIR spectroscopy, on the other hand, is more commonly used for qualitative analysis. Furthermore, Fourier transformation is a mathematical algorithm used to decode the interferogram and to obtain interpretable information about individual frequencies. The dispersive element of conventional infrared technique is replaced by Michelson interferometer. The interferometer encodes the incident frequencies, which are converted into a sinusoidal signal, of which is characteristic of each wavelength. Namely, FT-IR spectrometers have significant advantages over dispersive-type instruments [23] .
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A Modified Pass Based Identification Technique  to Make Zrp Secure

A Modified Pass Based Identification Technique to Make Zrp Secure

Jonny Karlsson, Laurence S. Dooley and Goran Pulkkis (2012) in their paper entitled "Safety routing in mobile ad hoc networks" presented a review of MANET routing protocols is briefly presented. MANET Security Attacks against routing can be and passive or active. The aim of the former is the search for information, monitoring of network traffic instance, while the second is performed by malicious nodes with the express intent to annoy, modify or discontinue MANET routing. An overview of active attacks based on modifying, impersonation / spoofing, manufacturing, wormhole, and selfish behavior is presented. The importance of cryptography and confidence in the MANET routing is secure also described, with relevant security extensions to existing routing protocols described and evaluated MANET. A comparison of existing secure routing protocols form the main contribution in this paper, while some future research challenges in the routing MANET secure are discussed.
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Observation on Therapeutic Plant Identification based on Deep Learning Technique

Observation on Therapeutic Plant Identification based on Deep Learning Technique

Abstract: Plants have been used for medicinal purposes long before recorded history. It plays a major role in medicines, food, perfumes and cosmetics industries. By knowing the herbal plants and its usage it can be used for above applications. In this digital era, people don’t have adequate knowledge to identify various herbal plants which are used by our ancestors for long time. Presently, the identification of herbal plants is purely based on the human perception or knowledge. There may be probability of human error occurring. In order to have an efficient herb species classification, there must be a complete model which should be automatic and convenient recognition system. This paper is reviewing the different leaf classification methodologies based on deep learning algorithms. The main aim of this research paper is to conclude the advanced technique for the leaf identification.
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Study and Analysis of Edge Detection Techniques in Digital Images Shiva Sharma *1 , Vandana Mahajan 2

Study and Analysis of Edge Detection Techniques in Digital Images Shiva Sharma *1 , Vandana Mahajan 2

The use of image processing helps to improve the image quality and analysis for different applications. This field has a broad spectrum of application such as remote sensing via satellite and other spacecrafts, image transmission and storage, medical, radar, sonar and acoustic image processing, robotics and automated inspection of industrial products. As an important image processing technique, edge detection plays a key role in practical applications such as medical science, remote sensing, satellite imaging and so on.

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Performance of Fractal Image Compression for Medical Images: A Comprehensive Literature Review

Performance of Fractal Image Compression for Medical Images: A Comprehensive Literature Review

From the above discussed fuzzy based methods, some contributor results are given here. The crisp approach tends to discard more information, whereas the fuzzy approach tends to preserve more image information by [78] is depicted in Figure 3, in which the proposed model does not include uncertainty generated by human perception of complexity. Therefore, the image complexity measure provided by the procedure is very consistent and can applicable for image edge detection task. The comparative experiment results by [104] are shown in Table 4. The results by [105] are depicted in Table 5 and Figure 4-5, shows that the proposed method for FIC is faster and remains better decoding image quality and can be applied to any image with different texture complexity, especially does better for an image with more complex texture.
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A HYBRID TECHNIQUE FOR FREQUENCY DOMAIN IDENTIFICATION OF SERVO SYSTEM WITH FRICTION FORCE

A HYBRID TECHNIQUE FOR FREQUENCY DOMAIN IDENTIFICATION OF SERVO SYSTEM WITH FRICTION FORCE

Chee Khiang Pang et al. [25] have developed a modal parametric identification method for linear-time- invariant flexible mechanical systems to assess residues, damping ratios, and natural frequencies of resonant modes. Two consequent least squares error optimization principle in modal summation structure has been utilized to optimize the coefficients and residues of the transfer function model. Experimental frequency responses measured by a laser doppler vibrometer from a commercial dual-stage hard disk drive has been used to prove the proposed methodology. Their results have confirmed that the proposed system identification algorithm was both effective and robust in estimating the modal parameters of adjustable mechanical constructs in mechatronic systems.
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Recognition of Handwritten Numerals of Manipuri Script

Recognition of Handwritten Numerals of Manipuri Script

Bangla, Devanagari. In 2005, S.Basu et.al [8] presented a MLP based technique where they used Shadow Features, Centriod Features, and Longest-run Features. The system was designed for recognition of Bangla handwritten characters and it performed well. Experimentally observed recognition accuracy was 86.46%. In 2007, U. Pal et.al [9], presented a MQDF based technique where they used directional information obtained from the arc tangent of the gradient. Using 5-fold cross validation technique they obtained 85.90% accuracy from a dataset of Bangla compound characters containing 20,543 samples.
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An Approach of Neural Networks to Apprehending of Gurmukhi character style

An Approach of Neural Networks to Apprehending of Gurmukhi character style

In this paper we evaluate an approach by construct a dataset which consists of Punjabi character images. These documents are noiseless and without skew and are written in various different font faces .The method has been implemented and evaluated using MATLAB tool, with a dual core, 2.60 GHz Intel Core i5 with 4GB RAM memory. The Common criteria for performance evaluation are based on the Accuracy (A).The accuracy of a measurement system is the degree of closeness of measurements of a quantity to that quantity's actual (true) value.
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Validation of a novel method for localization of parathyroid adenomas using SPECT/CT

Validation of a novel method for localization of parathyroid adenomas using SPECT/CT

The primary outcome was the accuracy of the novel technique of parathyroid adenoma localization based on SPECT/CT using intra-operative identification as the gold standard. The accuracy was compared to that of the original radiology report using cohen ’ s kappa. Our secondary outcomes were inter-rater reli- ability of using this novel technique. A clinical diag- nosis of PHPT included hypercalcemia and high PTH levels. Operative reports were used to identify the correct location of the adenoma causing hyperpara- thyroidism. Calcium, PTH, intraoperative identifica- tion of the adenoma location, radiology report identification, and the result of the performed task by participants were all recorded.
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Image Encryption and Decryption Using Image Gradient Technique

Image Encryption and Decryption Using Image Gradient Technique

Decryption is exactly the reverse procedure of encryption. When the receiver obtains three shares and encrypted image, extraction of the numbers from shares(random values and flag values) are to be done. This extraction of numbers from image is considered as the highlighting factor of this paper, since numbers are converted to bitmap image format which is a new concept introduced in this paper. The process of extracting numbers from the image and change in intensity of pixels in an image is called gradient technique. Therefore the title of the paper „Image gradient technique‟[5].
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Acinetobacter species identification by using tRNA spacer fingerprinting

Acinetobacter species identification by using tRNA spacer fingerprinting

Members of the genus Acinetobacter are short, plump, non- motile, gram-negative rods that are essentially nonmotile be- cause of the absence of flagellae. They are nonfastidious, cata- lase-positive, oxidase-negative strict aerobes that grow on simple media containing a single carbon source. The genus has been known for many years to be genotypically heterogeneous (12, 17, 19). In the absence of objective criteria for subdivision of the genus only one genus and species, Acinetobacter cal- coaceticus, was described in Bergey’s Manual of Systematic Bac- teriology (20). Many taxonomists have considered this classifi- cation insufficient given the considerable heterogeneity among members of the genus. Since 1986, DNA-DNA hybridization studies have resulted in the identification of 21 DNA groups (4, 5, 12, 13, 22, 24). Those studies were performed independently by different laboratories which has led to equivocal designa- tions for some of the groups that have been described lately (Table 1). Unfortunately, there is no single biochemical test or set of tests that enables the accurate identification of strains at the DNA group level.
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Hardening against adversarial examples with the smooth gradient
method

Hardening against adversarial examples with the smooth gradient method

The input update technique has been tested on some common benchmark computer vision datasets, frequently used to compare the performance of Deep Learning algorithms. Using computer vision tasks allows us also to visualise the gradients propagated back to the input, the updated inputs and the adversarial examples in a human–friendly manner. Our experimental methodology consists of running the same Convolutional Neural Network five times and reporting the median results. This is the same methodology as reported in [24]. We chose this methodology because it is in line with other results on the same datasets, and it allows us to produce effective results even in the case where the training is a very slow process 2 . We first generate our control experiment
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DNA and RNA analyses in detection of genetic predisposition to cancer

DNA and RNA analyses in detection of genetic predisposition to cancer

In the most popular variant of this technique, using agarose electrophoresis, not only flanking primers but also a primer fully complementary to the allele with a mutation or a primer of one which is complementary to the allele with a mutation and another to the wild allele are used. Primers are localized in such a way that different PCR products are of different length depending on the genotype of the examined DNA sample (Figure 9). The modern version of this technique uses short allele- specific probes and machines of real time PCR [22, 23]. This allows very fast analysis of many DNA samples. Technology using a template with oligonucleotides
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Smartphone Based Anti Spoofing Technique

Smartphone Based Anti Spoofing Technique

In spite of essential ongoing advances, there is an open drawback to the affectability of biometric frameworks to ridiculing assaults. On account of face bioscience, a satirizing assault comprises in exhibiting an imagine test (e.g., photos, advanced video, or 3D veil) to the procurement identifier with the facial data of a legitimate client. This paper[20] present another satirizing assault recognizing strategy with minimal effort and which is a product based technique. Relics can be explaine utilizing the highlights that we remove from the component of time- unearthly labels, which can be fathomed as a small-level component label that give brief and ghost data about the biometric test and use the visual codebook thought to find medium-level component labels that figured from the low- level component labels. Such labels are progressively enthusiastic for dismembering different sorts of attacks than the small-level ones.
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Identification of piecewise affine systems based on fuzzy PCA guided robust clustering technique

Identification of piecewise affine systems based on fuzzy PCA guided robust clustering technique

Hybrid systems are a class of dynamical systems whose behaviors are based on the interaction between discrete and continuous dynamical behaviors. Since a general method for the analysis of hybrid systems is not available, some researchers have focused on specific types of hybrid systems. Piecewise affine (PWA) systems are one of the subsets of hybrid systems. The identification of PWA systems includes the estimation of the parameters of affine subsystems and the coefficients of the hyperplanes defining the partition of the state-input domain. In this paper, we have proposed a PWA identification approach based on a modified clustering technique. By using a fuzzy PCA- guided robust k-means clustering algorithm along with neighborhood outlier detection, the two main drawbacks of the well-known clustering algorithms, i.e., the poor initialization and the presence of outliers, are eliminated. Furthermore, this modified clustering technique enables us to determine the number of subsystems without any prior knowledge about system. In addition, applying the structure of the state-input domain, that is, considering the time sequence of input-output pairs, provides a more efficient clustering algorithm, which is the other novelty of this work. Finally, the proposed algorithm has been evaluated by parameter identification of an IGV servo actuator. Simulation together with experiment analysis has proved the effectiveness of the proposed method.
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