Search results for: visual mon-negative matrix factorization model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19489

Search results for: visual mon-negative matrix factorization model

19339 Visual and Clinical Outcome in Patients with Corneal Lacerations

Authors: Avantika Verma

Abstract:

In industrialized nations, corneal lacerations are one of the most common reason for hospitalization. This study was designed to study visual and clinical outcome in patients presenting with full thickness corneal lacerations in Indian population and to ascertain the impact of various preoperative and operative factors influencing prognosis after repair of corneal lacerations. Males in third decade with injuries at work with metallic objects were common. Lens damage, hyphema, vitreous hemorrhage, retinal detachment and endophthalmitis were seen. All the patients underwent primary repair within first 24 hours of presentation. At 3 months, 74.3% had a good visual outcome. About 5.7% of patients had no perception of light.In conclusion, various demographic and preoperative factors like age, time of presentation, vision at presentation, length of corneal wound, involvement of visual axis, associated ocular features like hyphaema, lenticular changes, vitreous haemorrhage and retinal detachment are significant prognostic indicators for final visual outcome.

Keywords: corneal laceration, corneal wound repair, injury, visual outcome

Procedia PDF Downloads 324
19338 Efficient Reconstruction of DNA Distance Matrices Using an Inverse Problem Approach

Authors: Boris Melnikov, Ye Zhang, Dmitrii Chaikovskii

Abstract:

We continue to consider one of the cybernetic methods in computational biology related to the study of DNA chains. Namely, we are considering the problem of reconstructing the not fully filled distance matrix of DNA chains. When applied in a programming context, it is revealed that with a modern computer of average capabilities, creating even a small-sized distance matrix for mitochondrial DNA sequences is quite time-consuming with standard algorithms. As the size of the matrix grows larger, the computational effort required increases significantly, potentially spanning several weeks to months of non-stop computer processing. Hence, calculating the distance matrix on conventional computers is hardly feasible, and supercomputers are usually not available. Therefore, we started publishing our variants of the algorithms for calculating the distance between two DNA chains; then, we published algorithms for restoring partially filled matrices, i.e., the inverse problem of matrix processing. In this paper, we propose an algorithm for restoring the distance matrix for DNA chains, and the primary focus is on enhancing the algorithms that shape the greedy function within the branches and boundaries method framework.

Keywords: DNA chains, distance matrix, optimization problem, restoring algorithm, greedy algorithm, heuristics

Procedia PDF Downloads 69
19337 Parameterized Lyapunov Function Based Robust Diagonal Dominance Pre-Compensator Design for Linear Parameter Varying Model

Authors: Xiaobao Han, Huacong Li, Jia Li

Abstract:

For dynamic decoupling of linear parameter varying system, a robust dominance pre-compensator design method is given. The parameterized pre-compensator design problem is converted into optimal problem constrained with parameterized linear matrix inequalities (PLMI); To solve this problem, firstly, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameterized Lyapunov function (PLF) and pre-compensator. Then the problem was reduced to a normal convex optimization problem with normal linear matrix inequalities (LMI) constraints on a newly constructed convex polyhedron. Moreover, a parameter scheduling pre-compensator was achieved, which satisfies robust performance and decoupling performances. Finally, the feasibility and validity of the robust diagonal dominance pre-compensator design method are verified by the numerical simulation of a turbofan engine PLPV model.

Keywords: linear parameter varying (LPV), parameterized Lyapunov function (PLF), linear matrix inequalities (LMI), diagonal dominance pre-compensator

Procedia PDF Downloads 375
19336 An Information Matrix Goodness-of-Fit Test of the Conditional Logistic Model for Matched Case-Control Studies

Authors: Li-Ching Chen

Abstract:

The case-control design has been widely applied in clinical and epidemiological studies to investigate the association between risk factors and a given disease. The retrospective design can be easily implemented and is more economical over prospective studies. To adjust effects for confounding factors, methods such as stratification at the design stage and may be adopted. When some major confounding factors are difficult to be quantified, a matching design provides an opportunity for researchers to control the confounding effects. The matching effects can be parameterized by the intercepts of logistic models and the conditional logistic regression analysis is then adopted. This study demonstrates an information-matrix-based goodness-of-fit statistic to test the validity of the logistic regression model for matched case-control data. The asymptotic null distribution of this proposed test statistic is inferred. It needs neither to employ a simulation to evaluate its critical values nor to partition covariate space. The asymptotic power of this test statistic is also derived. The performance of the proposed method is assessed through simulation studies. An example of the real data set is applied to illustrate the implementation of the proposed method as well.

Keywords: conditional logistic model, goodness-of-fit, information matrix, matched case-control studies

Procedia PDF Downloads 265
19335 Electrospun Fibers Made from Biopolymers (Cellulose Acetate/Chitosan) for Metals Recovery

Authors: Mauricio Gómez, Esmeralda López, Ian Becar, Jaime Pizarro, Paula A. Zapata

Abstract:

A biodegradable material is developed with adsorptive capacity for metals ion for intended use in mining tailings mitigating the environmental impact with economic retribution, two types of fibers were elaborated by electrospinning: (1) a cellulose acetate (CA) matrix and (2) a cellulose acetate (CA)/chitosan (CH) matrix evaluating the effect of CH in CA on its physicochemical properties. Through diffuse reflectance infrared fourier transform spectroscopy (DRIFTS) the incorporation of chitosan in the matrix was identified, observing the band of the amino group at 1500 - 1600 [cm-1]. By scanning electron microscopy (SEM), Hg porosimetry, and CO2 isotherm at 273 [K], the intrafiber microporosity and interfiber macroporosity were identified, with an increase in the distribution of macropores for CA/CH fibers. In the tensile test, CH into the matrix produces a more ductile and tenacious behavior, where the % elongation at break increased by 33% with the other parameters constant. Thermal analysis by differential scanning calorimetry (DSC) and Thermogravimetric Analysis (TGA) showed that the incorporation of chitosan produces higher retention of water molecules due to the functional groups (amino groups (- NH3)), but there is a decrease in the specific heat and thermoplastic properties of the matrix since the glass transition temperature and softening temperature disappear. The effect of the optimum pH for CA and CA/CH fibers were studied in a batch system. In the adsorption kinetic study, the best isotherm model adapted to the experimental results corresponds to the Sips model and the kinetics corresponds to pseudo-second order

Keywords: environmental materials, wastewater treatment, electrospun fibers, biopolymers (cellulose acetate/chitosan), metals recovery

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19334 An Investigation of a Three-Dimensional Constitutive Model of Gas Diffusion Layers in Polymer Electrolyte Membrane Fuel Cells

Authors: Yanqin Chen, Chao Jiang, Chongdu Cho

Abstract:

This research presents the three-dimensional mechanical characteristics of a commercial gas diffusion layer by experiment and simulation results. Although the mechanical performance of gas diffusion layers has attracted much attention, its reliability and accuracy are still a major challenge. With the help of simulation analysis methods, it is beneficial to the gas diffusion layer’s extensive commercial development and the overall stress analysis of proton electrolyte membrane fuel cells during its pre-production design period. Therefore, in this paper, a three-dimensional constitutive model of a commercial gas diffusion layer, including its material stiffness matrix parameters, is developed and coded, in the user-defined material model of a commercial finite element method software for simulation. Then, the model is validated by comparing experimental results as well as simulation outcomes. As a result, both the experimental data and simulation results show a good agreement with each other, with high accuracy.

Keywords: gas diffusion layer, proton electrolyte membrane fuel cell, stiffness matrix, three-dimensional mechanical characteristics, user-defined material model

Procedia PDF Downloads 135
19333 Linear MIMO Model Identification Using an Extended Kalman Filter

Authors: Matthew C. Best

Abstract:

Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems.

Keywords: system identification, Kalman filter, linear model, MIMO, model order reduction

Procedia PDF Downloads 567
19332 Graph Similarity: Algebraic Model and Its Application to Nonuniform Signal Processing

Authors: Nileshkumar Vishnav, Aditya Tatu

Abstract:

A recent approach of representing graph signals and graph filters as polynomials is useful for graph signal processing. In this approach, the adjacency matrix plays pivotal role; instead of the more common approach involving graph-Laplacian. In this work, we follow the adjacency matrix based approach and corresponding algebraic signal model. We further expand the theory and introduce the concept of similarity of two graphs. The similarity of graphs is useful in that key properties (such as filter-response, algebra related to graph) get transferred from one graph to another. We demonstrate potential applications of the relation between two similar graphs, such as nonuniform filter design, DTMF detection and signal reconstruction.

Keywords: graph signal processing, algebraic signal processing, graph similarity, isospectral graphs, nonuniform signal processing

Procedia PDF Downloads 318
19331 Random Matrix Theory Analysis of Cross-Correlation in the Nigerian Stock Exchange

Authors: Chimezie P. Nnanwa, Thomas C. Urama, Patrick O. Ezepue

Abstract:

In this paper we use Random Matrix Theory to analyze the eigen-structure of the empirical correlations of 82 stocks which are consistently traded in the Nigerian Stock Exchange (NSE) over a 4-year study period 3 August 2009 to 26 August 2013. We apply the Marchenko-Pastur distribution of eigenvalues of a purely random matrix to investigate the presence of investment-pertinent information contained in the empirical correlation matrix of the selected stocks. We use hypothesised standard normal distribution of eigenvector components from RMT to assess deviations of the empirical eigenvectors to this distribution for different eigenvalues. We also use the Inverse Participation Ratio to measure the deviation of eigenvectors of the empirical correlation matrix from RMT results. These preliminary results on the dynamics of asset price correlations in the NSE are important for improving risk-return trade-offs associated with Markowitz’s portfolio optimization in the stock exchange, which is pursued in future work.

Keywords: correlation matrix, eigenvalue and eigenvector, inverse participation ratio, portfolio optimization, random matrix theory

Procedia PDF Downloads 311
19330 Stability Analysis of Rabies Model with Vaccination Effect and Culling in Dogs

Authors: Eti Dwi Wiraningsih, Folashade Agusto, Lina Aryati, Syamsuddin Toaha, Suzanne Lenhart, Widodo, Willy Govaerts

Abstract:

This paper considers a deterministic model for the transmission dynamics of rabies virus in the wild dogs-domestic dogs-human zoonotic cycle. The effect of vaccination and culling in dogs is considered on the model, then the stability was analysed to get basic reproduction number. We use the next generation matrix method and Routh-Hurwitz test to analyze the stability of the Disease-Free Equilibrium and Endemic Equilibrium of this model.

Keywords: stability analysis, rabies model, vaccination effect, culling in dogs

Procedia PDF Downloads 602
19329 Analysis of Artificial Hip Joint Using Finite Element Method

Authors: Syed Zameer, Mohamed Haneef

Abstract:

Hip joint plays very important role in human beings as it takes up the whole body forces generated due to various activities. These loads are repetitive and fluctuating depending on the activities such as standing, sitting, jogging, stair casing, climbing, etc. which may lead to failure of Hip joint. Hip joint modification and replacement are common in old aged persons as well as younger persons. In this research study static and Fatigue analysis of Hip joint model was carried out using finite element software ANSYS. Stress distribution obtained from result of static analysis, material properties and S-N curve data of fabricated Ultra High molecular weight polyethylene / 50 wt% short E glass fibres + 40 wt% TiO2 Polymer matrix composites specimens were used to estimate fatigue life of Hip joint using stiffness Degradation model for polymer matrix composites. The stress distribution obtained from static analysis was found to be within the acceptable range.The factor of safety calculated from linear Palmgren linear damage rule is less than one, which indicates the component is safe under the design.

Keywords: hip joint, polymer matrix composite, static analysis, fatigue analysis, stress life approach

Procedia PDF Downloads 323
19328 Event Related Potentials in Terms of Visual and Auditory Stimuli

Authors: Seokbeen Lim, KyeongSeok Sim, DaKyeong Shin, Gilwon Yoon

Abstract:

Event-related potential (ERP) is one of the useful tools for investigating cognitive reactions. In this study, the potential of ERP components detected after auditory and visual stimuli was examined. Subjects were asked to respond upon stimuli that were of three categories; Target, Non-Target and Standard stimuli. The ERP after stimulus was measured. In the experiment of visual evoked potentials (VEPs), the subjects were asked to gaze at a center point on the monitor screen where the stimuli were provided by the reversal pattern of the checkerboard. In consequence of the VEP experiments, we observed consistent reactions. Each peak voltage could be measured when the ensemble average was applied. Visual stimuli had smaller amplitude and a longer latency compared to that of auditory stimuli. The amplitude was the highest with Target and the smallest with Standard in both stimuli.

Keywords: auditory stimulus, EEG, event related potential, oddball task, visual stimulus

Procedia PDF Downloads 256
19327 Ologen Collagen Matrix Implant in Uveitis Induced Glaucoma with Temporal Trabeculectomy

Authors: Ritesh Verma, Manisha Rathi, Chand Singh Dhull, Sumit Sachdeva, Jitender Phogat

Abstract:

Temporal trabeculectomy with the Ologen implant was done in a 66-year-old lady with uveitic glaucoma. Serial IOP measurement was done to assess the efficacy of ologen implant in uveitic glaucoma. The patient had an IOP of 4mmhg day 1 postoperatively and Ologen implant was in place with a well-formed bleb. On follow up patient had an IOP of 14mmhg and unaided visual acuity of 6/12 on day 10 postoperatively. After 12 weeks of Trabeculectomy with Ologen implant, the IOP of the patient was 14 mmHg, the vision was 6/6 with -1.25 DS and -1.25 DC at 90 degrees. Trabeculectomy performed in patients with uveitic glaucoma has a higher chance of failure due to increased inflammation and fibrosis. Trabeculectomy with ologen implant done in a patient of uveitic glaucoma provides excellent postoperative results and the patient has a well-controlled IOP even after 56 weeks of surgery and a best corrected visual acuity of 6/6. Trabeculectomy with the ologen implant is superior to other surgeries in cases of secondary glaucoma with increased inflammation.

Keywords: glaucoma surgery, ologen implant, temporal trabeculectomy, uveitic glaucoma

Procedia PDF Downloads 182
19326 The Norm, Singular Value and Condition Number Analysis for the Hadamard Matrices

Authors: Emine Tuğba Akyüz

Abstract:

In this study, the analysis of Hadamard matrices, which is a special type of matrix, was made under three headings: norms, singular values, condition number. Six norm types was applied to Hadamard matrices and the relationship between the results and the size of the matrix has been studied. As a result of the investigation when 2-norm was used on the problem Hx =f, the equation ‖x‖_2= ‖f‖_2/√n was shown (H is n-dimensional Hadamard matrix). Related with this, the relationship between the the singular value of H and 2-norm and eigenvalues was shown. Then, the evaluation of condition number for Hx =f was made.

Keywords: condition number, Hadamard matrix, norm, singular value

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19325 Cantilever Secant Pile Constructed in Sand: Capping Beam Analysis and Design - Part I

Authors: Khaled R. Khater

Abstract:

The paper theme is soil retaining structures. Cantilever secant-pile wall is triggering scientific point of curiosity. Specially the capping beams structural analysis and its interaction with secant piles as one integrated matrix. It is believed that straining actions of this integrated matrix are most probably induced due to a combination of induced line load and non-uniform horizontal pile tips displacement. The strategy that followed throughout this study starts by converting the pile head horizontal displacements generated by Plaxis-2D model to a system of concentrated line load acting per meter run along the capping beam. Then, those line loads are the input data of Staad-Pro 3D-model. Those models tailored to allow the capping beam and the secant piles interacting as one matrix, i.e. a unit. It is believed that the suggested strategy presents close to real structural simulation. The above is the paper thought and methodology. Three sand densities, one pile rigidity and one excavation depth, “h = 4.0-m,” are completely sufficient to achieve the paper’s objective.

Keywords: secant piles, capping beam, analysis, design, plaxis 2D, staad pro 3D

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19324 Computer Simulations of Stress Corrosion Studies of Quartz Particulate Reinforced ZA-27 Metal Matrix Composites

Authors: K. Vinutha

Abstract:

The stress corrosion resistance of ZA-27 / TiO2 metal matrix composites (MMC’s) in high temperature acidic media has been evaluated using an autoclave. The liquid melt metallurgy technique using vortex method was used to fabricate MMC’s. TiO2 particulates of 50-80 µm in size are added to the matrix. ZA-27 containing 2,4,6 weight percentage of TiO2 are prepared. Stress corrosion tests were conducted by weight loss method for different exposure time, normality and temperature of the acidic medium. The corrosion rates of composites were lower to that of matrix ZA-27 alloy under all conditions.

Keywords: autoclave, MMC’s, stress corrosion, vortex method

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19323 The Design of a Vehicle Traffic Flow Prediction Model for a Gauteng Freeway Based on an Ensemble of Multi-Layer Perceptron

Authors: Tebogo Emma Makaba, Barnabas Ndlovu Gatsheni

Abstract:

The cities of Johannesburg and Pretoria both located in the Gauteng province are separated by a distance of 58 km. The traffic queues on the Ben Schoeman freeway which connects these two cities can stretch for almost 1.5 km. Vehicle traffic congestion impacts negatively on the business and the commuter’s quality of life. The goal of this paper is to identify variables that influence the flow of traffic and to design a vehicle traffic prediction model, which will predict the traffic flow pattern in advance. The model will unable motorist to be able to make appropriate travel decisions ahead of time. The data used was collected by Mikro’s Traffic Monitoring (MTM). Multi-Layer perceptron (MLP) was used individually to construct the model and the MLP was also combined with Bagging ensemble method to training the data. The cross—validation method was used for evaluating the models. The results obtained from the techniques were compared using predictive and prediction costs. The cost was computed using combination of the loss matrix and the confusion matrix. The predicted models designed shows that the status of the traffic flow on the freeway can be predicted using the following parameters travel time, average speed, traffic volume and day of month. The implications of this work is that commuters will be able to spend less time travelling on the route and spend time with their families. The logistics industry will save more than twice what they are currently spending.

Keywords: bagging ensemble methods, confusion matrix, multi-layer perceptron, vehicle traffic flow

Procedia PDF Downloads 313
19322 SiamMask++: More Accurate Object Tracking through Layer Wise Aggregation in Visual Object Tracking

Authors: Hyunbin Choi, Jihyeon Noh, Changwon Lim

Abstract:

In this paper, we propose SiamMask++, an architecture that performs layer-wise aggregation and depth-wise cross-correlation and introduce multi-RPN module and multi-MASK module to improve EAO (Expected Average Overlap), a representative performance evaluation metric for Visual Object Tracking (VOT) challenge. The proposed architecture, SiamMask++, has two versions, namely, bi_SiamMask++, which satisfies the real time (56fps) on systems equipped with GPUs (Titan XP), and rf_SiamMask++, which combines mask refinement modules for EAO improvements. Tests are performed on VOT2016, VOT2018 and VOT2019, the representative datasets of Visual Object Tracking tasks labeled as rotated bounding boxes. SiamMask++ perform better than SiamMask on all the three datasets tested. SiamMask++ is achieved performance of 62.6% accuracy, 26.2% robustness and 39.8% EAO, especially on the VOT2018 dataset. Compared to SiamMask, this is an improvement of 4.18%, 37.17%, 23.99%, respectively. In addition, we do an experimental in-depth analysis of how much the introduction of features and multi modules extracted from the backbone affects the performance of our model in the VOT task.

Keywords: visual object tracking, video, deep learning, layer wise aggregation, Siamese network

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19321 Development of Noninvasive Method to Analyze Dynamic Changes of Matrix Stiffness and Elasticity Characteristics

Authors: Elena Petersen, Inna Kornienko, Svetlana Guryeva, Sergey Dobdin, Anatoly Skripal, Andrey Usanov, Dmitry Usanov

Abstract:

One of the most important unsolved problems in modern medicine is the increase of chronic diseases that lead to organ dysfunction or even complete loss of function. Current methods of treatment do not result in decreased mortality and disability statistics. Currently, the best treatment for many patients is still transplantation of organs and/or tissues. Therefore, finding a way of correct artificial matrix biofabrication in case of limited number of natural organs for transplantation is a critical task. One important problem that needs to be solved is development of a nondestructive and noninvasive method to analyze dynamic changes of mechanical characteristics of a matrix with minimal side effects on the growing cells. This research was focused on investigating the properties of matrix as a marker of graft condition. In this study, the collagen gel with human primary dermal fibroblasts in suspension (60, 120, 240*103 cells/mL) and collagen gel with cell spheroids were used as model objects. The stiffness and elasticity characteristics were evaluated by a semiconductor laser autodyne. The time and cell concentration dependency of the stiffness and elasticity were investigated. It was shown that these properties changed in a non-linear manner with respect to cell concentration. The maximum matrix stiffness was observed in the collagen gel with the cell concentration of 120*103 cells/mL. This study proved the opportunity to use the mechanical properties of matrix as a marker of graft condition, which can be measured by noninvasive semiconductor laser autodyne technique.

Keywords: graft, matrix, noninvasive method, regenerative medicine, semiconductor laser autodyne

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19320 The Relation between Learning Styles and English Achievement in the Language Training Centre

Authors: Nurul Yusnita

Abstract:

Many studies have been developed to help the students to get good achievement in English learning. They can be from the teaching method or psychological ones. One of the psychological studies in educational research is learning style. In some ways, learning style can affect the achievement of the students. This study aimed to examine 4 (four) learning styles and their relations to English achievement among the students learning English in Language Training Center of Universitas Muhammadiyah Yogyakarta (LTC UMY). The method of this study was descriptive analytical. The sample consisted of 39 Accounting students in LTC UMY. The data was collected through questionnaires with Likert-scale. The achievement was obtained from the grade of the students. To analyze the questionnaires and to see the relation between the learning styles and the student achievement, SPSS statistical software of correlational analysis was used. The result showed that both visual and auditory had the same percentage of 35.9% (14 students). 3 students (7.7%) had kinaesthetic learning style and 8 students (20.5%) had visual and auditory ones. Meanwhile, there were 5 students (12.8%) who had visual learning style could increase their grades. Only 1 student (2.5%) who had visual and auditory could improve his grade. Besides grade increase, there were also grade decrease. Students with visual, auditory, visual and auditory, and kinaesthetic learning styles were 3 students (7.7%), 5 students (12%), 4 students (10.2%) and 1 student (2.5%) respectively. In conclusion, there was no significant relationship between learning style and English achievement. Most of the good achievers were the students with visual and auditory learning styles and most of them preferred visual method. The implication is the teachers and material designers could improve their method through visual things to achieve effective English teaching learning.

Keywords: accounting students, English achievement, language training centre, learning styles

Procedia PDF Downloads 235
19319 On Parameter Estimation of Simultaneous Linear Functional Relationship Model for Circular Variables

Authors: N. A. Mokhtar, A. G. Hussin, Y. Z. Zubairi

Abstract:

This paper proposes a new simultaneous simple linear functional relationship model by assuming equal error variances. We derive the maximum likelihood estimate of the parameters in the simultaneous model and the covariance. We show by simulation study the small bias values of the parameters suggest the suitability of the estimation method. As an illustration, the proposed simultaneous model is applied to real data of the wind direction and wave direction measured by two different instruments.

Keywords: simultaneous linear functional relationship model, Fisher information matrix, parameter estimation, circular variables

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19318 Comparison between Separable and Irreducible Goppa Code in McEliece Cryptosystem

Authors: Newroz Nooralddin Abdulrazaq, Thuraya Mahmood Qaradaghi

Abstract:

The McEliece cryptosystem is an asymmetric type of cryptography based on error correction code. The classical McEliece used irreducible binary Goppa code which considered unbreakable until now especially with parameter [1024, 524, and 101], but it is suffering from large public key matrix which leads to be difficult to be used practically. In this work Irreducible and Separable Goppa codes have been introduced. The Irreducible and Separable Goppa codes used are with flexible parameters and dynamic error vectors. A Comparison between Separable and Irreducible Goppa code in McEliece Cryptosystem has been done. For encryption stage, to get better result for comparison, two types of testing have been chosen; in the first one the random message is constant while the parameters of Goppa code have been changed. But for the second test, the parameters of Goppa code are constant (m=8 and t=10) while the random message have been changed. The results show that the time needed to calculate parity check matrix in separable are higher than the one for irreducible McEliece cryptosystem, which is considered expected results due to calculate extra parity check matrix in decryption process for g2(z) in separable type, and the time needed to execute error locator in decryption stage in separable type is better than the time needed to calculate it in irreducible type. The proposed implementation has been done by Visual studio C#.

Keywords: McEliece cryptosystem, Goppa code, separable, irreducible

Procedia PDF Downloads 237
19317 Quantum Statistical Machine Learning and Quantum Time Series

Authors: Omar Alzeley, Sergey Utev

Abstract:

Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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19316 Non-Targeted Adversarial Image Classification Attack-Region Modification Methods

Authors: Bandar Alahmadi, Lethia Jackson

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Machine Learning model is used today in many real-life applications. The safety and security of such model is important, so the results of the model are as accurate as possible. One challenge of machine learning model security is the adversarial examples attack. Adversarial examples are designed by the attacker to cause the machine learning model to misclassify the input. We propose a method to generate adversarial examples to attack image classifiers. We are modifying the successfully classified images, so a classifier misclassifies them after the modification. In our method, we do not update the whole image, but instead we detect the important region, modify it, place it back to the original image, and then run it through a classifier. The algorithm modifies the detected region using two methods. First, it will add abstract image matrix on back of the detected image matrix. Then, it will perform a rotation attack to rotate the detected region around its axes, and embed the trace of image in image background. Finally, the attacked region is placed in its original position, from where it was removed, and a smoothing filter is applied to smooth the background with foreground. We test our method in cascade classifier, and the algorithm is efficient, the classifier confident has dropped to almost zero. We also try it in CNN (Convolutional neural network) with higher setting and the algorithm was successfully worked.

Keywords: adversarial examples, attack, computer vision, image processing

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19315 Investigation of the Functional Impact of Amblyopia on Visual Skills in Children

Authors: Chinmay V. Deshpande

Abstract:

Purpose: To assess the efficiency of visual functions and visual skills in strabismic & anisometropic amblyopes and to assess visual acuity and contrast sensitivity in anisometropic amblyopes with spectacles & contact lenses. Method: In a prospective clinical study, 32 children ageing from 5 to 15 years presenting with amblyopia in a pediatric department of Shri Ganapati Netralaya Jalna, India, were assessed for a period of three & half months. Visual acuity was measured with Snellen’s and Bailey-Lovie log MAR charts whereas contrast sensitivity was measured with Pelli-Robson chart with spectacles and contact lenses. Saccadic movements were assessed with SCCO scoring criteria and accommodative facility was checked with ±1.50 DS flippers. Stereopsis was assessed with TNO test. Results: By using Wilcoxon sign rank test p-value < 0.05 (< 0.001), the mean linear visual acuity was 0.29 (≈ 6/21) and mean single optotype visual acuity found to be 0.36 (≈ 6/18). Mean visual acuity of 0.27(≈ 6/21) with spectacles improved to 0.33 (≈ 6/18) with contact lenses in amblyopic eyes. The mean Log MAR visual acuity with spectacles and contact lens were found to be 0.602( ≈6/24) and 0.531(≈ 6/21) respectively. The contrast threshold out of 20 amblyopic eyes shows that mean contrast threshold changed in 9 patients from spectacles 0.27 to contact lens 0.19 respectively. The mean accommodative facility assessed was 5.31(± 2.37). 24 subjects (75%) revealed marked saccadic defects on the test applied. 78% subjects didn’t show even gross stereoscopic ability on TNO test. Conclusion: This study supports the facts about amblyopia and associated deficits in visual skills which are claimed in previous studies. In addition, anisometropic amblyopia can be managed better with contact lenses.

Keywords: strabismus, anisometropia, amblyopia, contrast sensitivity, saccades, stereopsis

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19314 Transmission Line Matrix (TLM) Modelling of Microstrip Circular Antenna

Authors: Jugoslav Jokovic, Tijana Dimitrijevic, Nebojsa Doncov

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The goal of this paper is to investigate the possibilities and effectiveness of the TLM (Transmission Line Matrix) method for modelling of up-to-date microstrip antennas with circular geometry that have significant application in modern wireless communication systems. The coaxially fed microstrip antenna configurations with circular patch are analyzed by using the in-house 3DTLMcyl_cw solver based on computational electromagnetic TLM method adapted to the cylindrical grid and enhanced with the compact wire model. Opposed to the widely used rectangular TLM mesh, where a staircase approximation has to be used to describe curved boundaries, precise modelling of circular boundaries can be accomplished in the cylindrical grid irrespective of the mesh resolution. Using the compact wire model incorporated in cylindrical mesh, it is possible to model coaxial feed and include the influence of the real excitation in the antenna model. The conventional and inverted configuration of a coaxially fed circular patch antenna are considered, comparing the resonances obtained using TLM cylindrical model with results reached by the corresponding model in a rectangular grid as well as with experimental ones. Bearing in mind that accuracy of simulated results depends on a relevantly created model, besides structure geometry and dimensions, it is important to consider additional modelling issues, regarding appropriate mesh resolution and a relevant extension of a mesh around the considered structure that would provide convergence of the results.

Keywords: computational electromagnetic, coaxial feed, microstrip antenna, TLM modelling

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19313 Retention Properties of the Matrix Material Fe-Mn-Cu-Sn-C in Relation to Diamond Particles

Authors: Elżbieta Cygan-Bączek, Piotr Wyżga, Sławomir Cygan

Abstract:

In the presented work, the main goal was to investigate the retention properties, defined as the ability of the matrix material to hold diamond particles in relation to metallized (Ti, Si, Cr, Co, Cu, Ni) and non-metallized diamond crystals. For this purpose, diamond-impregnated specimens were tested for wear rate on abrasive sandstone using a test rig specially designed to simulate tool application conditions. The tests that involved 3- and 2-body abrasion ranked the alloys in different orders. The ability of the matrix to retain diamond crystals was determined using the electron microskopy (SEM, TEM). The specimens were also characterized by X-ray diffraction (XRD) and hardness. The conducted research has shown that Si and Ti metallized diamonds, apart from mechanical jamming in the matrix, are also connected in a metallurgical manner, ensuring the improvement of the retention properties of the matrix material.

Keywords: diamond, metallic-diamond segments, retention, abrasive wear resistance

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19312 Ophthalmic Hashing Based Supervision of Glaucoma and Corneal Disorders Imposed on Deep Graphical Model

Authors: P. S. Jagadeesh Kumar, Yang Yung, Mingmin Pan, Xianpei Li, Wenli Hu

Abstract:

Glaucoma is impelled by optic nerve mutilation habitually represented as cupping and visual field injury frequently with an arcuate pattern of mid-peripheral loss, subordinate to retinal ganglion cell damage and death. Glaucoma is the second foremost cause of blindness and the chief cause of permanent blindness worldwide. Consequently, all-embracing study into the analysis and empathy of glaucoma is happening to escort deep learning based neural network intrusions to deliberate this substantial optic neuropathy. This paper advances an ophthalmic hashing based supervision of glaucoma and corneal disorders preeminent on deep graphical model. Ophthalmic hashing is a newly proposed method extending the efficacy of visual hash-coding to predict glaucoma corneal disorder matching, which is the faster than the existing methods. Deep graphical model is proficient of learning interior explications of corneal disorders in satisfactory time to solve hard combinatoric incongruities using deep Boltzmann machines.

Keywords: corneal disorders, deep Boltzmann machines, deep graphical model, glaucoma, neural networks, ophthalmic hashing

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19311 Experimental Investigation and Analysis of Wear Parameters on Al/Sic/Gr: Metal Matrix Hybrid Composite by Taguchi Method

Authors: Rachit Marwaha, Rahul Dev Gupta, Vivek Jain, Krishan Kant Sharma

Abstract:

Metal matrix hybrid composites (MMHCs) are now gaining their usage in aerospace, automotive and other industries because of their inherent properties like high strength to weight ratio, hardness and wear resistance, good creep behaviour, light weight, design flexibility and low wear rate etc. Al alloy base matrix reinforced with silicon carbide (10%) and graphite (5%) particles was fabricated by stir casting process. The wear and frictional properties of metal matrix hybrid composites were studied by performing dry sliding wear test using pin on disc wear test apparatus. Experiments were conducted based on the plan of experiments generated through Taguchi’s technique. A L9 Orthogonal array was selected for analysis of data. Investigation to find the influence of applied load, sliding speed and track diameter on wear rate as well as coefficient of friction during wearing process was carried out using ANOVA. Objective of the model was chosen as smaller the better characteristics to analyse the dry sliding wear resistance. Results show that track diameter has highest influence followed by load and sliding speed.

Keywords: Taguchi method, orthogonal array, ANOVA, metal matrix hybrid composites

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19310 Exploring Time-Series Phosphoproteomic Datasets in the Context of Network Models

Authors: Sandeep Kaur, Jenny Vuong, Marcel Julliard, Sean O'Donoghue

Abstract:

Time-series data are useful for modelling as they can enable model-evaluation. However, when reconstructing models from phosphoproteomic data, often non-exact methods are utilised, as the knowledge regarding the network structure, such as, which kinases and phosphatases lead to the observed phosphorylation state, is incomplete. Thus, such reactions are often hypothesised, which gives rise to uncertainty. Here, we propose a framework, implemented via a web-based tool (as an extension to Minardo), which given time-series phosphoproteomic datasets, can generate κ models. The incompleteness and uncertainty in the generated model and reactions are clearly presented to the user via the visual method. Furthermore, we demonstrate, via a toy EGF signalling model, the use of algorithmic verification to verify κ models. Manually formulated requirements were evaluated with regards to the model, leading to the highlighting of the nodes causing unsatisfiability (i.e. error causing nodes). We aim to integrate such methods into our web-based tool and demonstrate how the identified erroneous nodes can be presented to the user via the visual method. Thus, in this research we present a framework, to enable a user to explore phosphorylation proteomic time-series data in the context of models. The observer can visualise which reactions in the model are highly uncertain, and which nodes cause incorrect simulation outputs. A tool such as this enables an end-user to determine the empirical analysis to perform, to reduce uncertainty in the presented model - thus enabling a better understanding of the underlying system.

Keywords: κ-models, model verification, time-series phosphoproteomic datasets, uncertainty and error visualisation

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