Search results for: modified simplex algorithm

Authors: Jae-Joon Song, Sang-Yoon Lee, Bong-Chul Joo

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The girder-type precast modular bridge has been developed as a simply supported bridge. The girder-type precast modular bridge could be applied to the multi-span bridges through the continuity method. The continuity of the girder-type precast modular bridge is achieved by using the link slab which is easy to construction and appropriate to the rapid construction. In this study, the link slab with transition zone was used for the continuity of the precast modular bridges, and the construction detail of link slab was modified. In addition, the modified iterative design method of link slab was proposed in this study. To verify the proposed design method, the fatigue test using the mock-up specimen was conducted with cycle loading condition up to two million cycles.

Keywords: precast, modular bridge, link slab

Procedia PDF Downloads 437

Authors: Korosh Khorshidi, Mohammad Khodadadi

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In this paper, exact close form solution for out of plate free flexural vibration of moderately thick rectangular nanoplates are presented based on nonlocal modified trigonometric shear deformation theory, with assumptions of the Levy's type boundary conditions, for the first time. The aim of this study is to evaluate the effect of small-scale parameters on the frequency parameters of the moderately thick rectangular nano-plates. To describe the effects of small-scale parameters on vibrations of rectangular nanoplates, the Eringen theory is used. The Levy's type boundary conditions are combination of six different boundary conditions; specifically, two opposite edges are simply supported and any of the other two edges can be simply supported, clamped or free. Governing equations of motion and boundary conditions of the plate are derived by using the Hamilton’s principle. The present analytical solution can be obtained with any required accuracy and can be used as benchmark. Numerical results are presented to illustrate the effectiveness of the proposed method compared to other methods reported in the literature. Finally, the effect of boundary conditions, aspect ratios, small scale parameter and thickness ratios on nondimensional natural frequency parameters and frequency ratios are examined and discussed in detail.

Keywords: exact solution, nonlocal modified sinusoidal shear deformation theory, out of plane vibration, moderately thick rectangular plate

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Authors: Wikanda Phaphan

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Mixture generalized gamma distribution is a combination of two distributions: generalized gamma distribution and length biased generalized gamma distribution. These two distributions were presented by Suksaengrakcharoen and Bodhisuwan in 2014. The findings showed that probability density function (pdf) had fairly complexities, so it made problems in estimating parameters. The problem occurred in parameter estimation was that we were unable to calculate estimators in the form of critical expression. Thus, we will use numerical estimation to find the estimators. In this study, we presented a new method of the parameter estimation by using the expectation – maximization algorithm (EM), the conjugate gradient method, and the quasi-Newton method. The data was generated by acceptance-rejection method which is used for estimating α, β, λ and p. λ is the scale parameter, p is the weight parameter, α and β are the shape parameters. We will use Monte Carlo technique to find the estimator's performance. Determining the size of sample equals 10, 30, 100; the simulations were repeated 20 times in each case. We evaluated the effectiveness of the estimators which was introduced by considering values of the mean squared errors and the bias. The findings revealed that the EM-algorithm had proximity to the actual values determined. Also, the maximum likelihood estimators via the conjugate gradient and the quasi-Newton method are less precision than the maximum likelihood estimators via the EM-algorithm.

Keywords: conjugate gradient method, quasi-Newton method, EM-algorithm, generalized gamma distribution, length biased generalized gamma distribution, maximum likelihood method

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Authors: Gursimran Jandu, Melissa Nelson, Mia Ingram, Hana Jalal

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There is a significant overlap between autism spectrum disorder (ASD) and obsessive-compulsive disorder (OCD), with up to 90% of young people diagnosed with ASD having this co-morbidity. Distinguishing between the symptoms of the two leads to issues with accurate treatment, yet this is paramount in benefiting the young person. There are two distinct methods of treatment, psychological or pharmacological, with clinicians tending to choose one or the other, potentially due to the lack of research available. This report reviews the efficacy of psychological and pharmacological treatments for young people diagnosed with ASD and co-morbid OCD. A literature review was performed on papers from the last fifteen years including ‘ASD’, ‘OCD’ and individuals under the age of 18. Eleven papers were selected as relevant. The report looks at the comparison between more traditional methods, such as selective-serotonin-reuptake-inhibitors (SSRI) and Cognitive behaviour therapy (CBT), and newer therapies, such as modified or intensive ASD focused psychotherapies, and the use of other medication classes. On reviewing the data, it was identified that there was a distinct lack of information on this important topic. The most widely used treatment was medication such as Fluoxetine, an SSRI, which rarely showed improvement in symptoms or outcomes. This is in contrast to modified forms of CBT which often reduces symptoms or even results in OCD remission. With increased research into non-traditional management of these co-morbid conditions, it is clear there is scope that modified CBT may become the future treatment of choice for OCD in young people with ASD.

Keywords: autism spectrum disorder, intensive or adapted cognitive behavioural therapy, obsessive compulsive disorder, pharmacological management

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Authors: Reza Babajanivalashedi, Stefania Lo Feudo, Jean-Luc Dion

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Liquid sloshing is a crucial problem for the dynamic of moving containers in the packaging industries. Sloshing issues have been so far mainly modeled within the framework of fluid dynamics or by using equivalent mechanical models with different kinds of movements and shapes of containers. Nevertheless, these approaches do not allow to determinate the shape of the free surface of the liquid in case of the irregular shape of the moving containers, so that experimental measurements may be required. If there is too much slosh in the moving tank, the liquid can be splashed out on the packages. So, the free surface oscillation must be controlled/reduced to eliminate the splashing. The purpose of this research is to propose an optimization algorithm for finding an optimum command law to reduce surface elevation. In the first step, the free surface of the liquid is simulated based on the separation variable and weak formulation models. Then Genetic and Gradient algorithms are developed for finding the optimum command law. The optimum command law is compared with existing command laws, and the results show that there is a significant difference in surface oscillation between optimum and existing command laws. This algorithm is applicable for different varieties of bottles in case of using the camera for detecting the liquid elevation, and it can produce new command laws for different kinds of tanks to reduce the surface oscillation and remove the splashing phenomenon.

Keywords: sloshing phenomenon, separation variables, weak formulation, optimization algorithm, command law

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Authors: Bachir Bentouati, Lakhdar Chaib, Saliha Chettih, Gai-Ge Wang

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The problem of economic dispatch (ED) is the basic problem of power framework, its main goal is to find the most favorable generation dispatch to generate each unit, reduce the whole power generation cost, and meet all system limitations. A heuristic algorithm, recently developed called Stud Krill Herd (SKH), has been employed in this paper to treat non-convex ED problems. The proposed KH has been modified using Stud selection and crossover (SSC) operator, to enhance the solution quality and avoid local optima. We are demonstrated SKH effects in two case study systems composed of 13-unit and 40-unit test systems to verify its performance and applicability in solving the ED problems. In the above systems, SKH can successfully obtain the best fuel generator and distribute the load requirements for the online generators. The results showed that the use of the proposed SKH method could reduce the total cost of generation and optimize the fulfillment of the load requirements.

Keywords: stud krill herd, economic dispatch, crossover, stud selection, valve-point effect

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Authors: Francis O. Nwawuru, Jeremiah N. Ezeora

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In this paper, a new algorithm for solving the system of split equilibrium and fixed point problems in real Hilbert spaces is considered. The equilibrium bifunction involves a nite family of pseudo-monotone mappings, which is an improvement over monotone operators. More so, it turns out that the solution of the finite family of nonexpansive mappings. The regularized parameters do not depend on Lipschitz constants. Also, the computations of the stepsize, which plays a crucial role in the convergence analysis of the proposed method, do require prior knowledge of the norm of the involved bounded linear map. Furthermore, to speed up the rate of convergence, an inertial term technique is introduced in the proposed method. Under standard assumptions on the operators and the control sequences, using a modified Halpern iteration method, we establish strong convergence, a desired result in applications. Finally, the proposed scheme is applied to solve some optimization problems. The result obtained improves numerous results announced earlier in this direction.

Keywords: equilibrium, Hilbert spaces, fixed point, nonexpansive mapping, extragradient method, regularized equilibrium

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Authors: S. Gómez, G. Sánchez, J. Zarama, M. Castañeda Ramos, J. Escoto Alcántar, J. Torres, A. Núñez, S. Santana, F. Nájera, J. A. Lopez

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This paper shows in detail the mathematical model of direct and inverse kinematics for a robot manipulator (welding type) with four degrees of freedom. Using the D-H parameters, screw theory, numerical, geometric and interpolation methods, the theoretical and practical values of the position of robot were determined using an optimized algorithm for inverse kinematics obtaining the values of the particular joints in order to determine the virtual paths in a relatively short time.

Keywords: kinematics, degree of freedom, optimization, robot manipulator

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Authors: Avatharam Ganivada, Krishna Shah

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The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.

Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision

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Authors: Muhammad Rana, Quazi Mamun, Rafiqul Islam

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In the Internet of Things (IoT), many devices are connected and accumulate a sheer amount of data. These Internet-driven raw data need to be transferred securely to the end-users via dependable networks. Consequently, the challenges of IoT security in various IoT domains are paramount. Cryptography is being applied to secure the networks for authentication, confidentiality, data integrity and access control. However, due to the resource constraint properties of IoT devices, the conventional cipher may not be suitable in all IoT networks. This paper designs a robust and effective lightweight cipher to secure the IoT environment and meet the resource-constrained nature of IoT devices. We also propose a symmetric and block-cipher based lightweight cryptographic algorithm. The proposed algorithm increases the complexity of the block cipher, maintaining the lowest computational requirements possible. The proposed algorithm efficiently constructs the key register updating technique, reduces the number of encryption rounds, and adds a new layer between the encryption and decryption processes.

Keywords: internet of things, cryptography block cipher, S-box, key management, security, network

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Authors: Debasis Sarkar

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This paper aims to apply the Grasshopper-Optimization-Algorithm (GOA) for designing and developing a Net-Zero-Energy residential building for a mega-city like Ahmedabad in India. The methodology implemented includes advanced tools like Revit for model creation and MATLAB for simulation, enabling the optimization of the building design. GOA has been applied in reducing cooling loads and overall energy consumption through optimized passive design features. For the attainment of a net zero energy mission, solar panels were installed on the roof of the building. It has been observed that the energy consumption of 8490 kWh was supported by the installed solar panels. Thereby only 840kWh had to be supported by non-renewable energy sources. The energy consumption was further reduced through the application of simulation and optimization methods like GOA, which further reduced the energy consumption to about 37.56 kWh per month from April to July when energy demand was at its peak. This endeavor aimed to achieve near-zero-energy consumption, showcasing the potential of renewable energy integration in building sustainability.

Keywords: grasshopper optimization algorithm, net zero energy, residential building, sustainable design

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Authors: Bin Mu, Site Li, Shijin Yuan

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Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.

Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model

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Authors: Hanaa A. S. Oraby, Amal A. M. Hassan, Mahmoud M. Sakr, Atef A. A. Haiba

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Applying the profiling approach for the assessment of proteomic variations due to genetic modification of the Egyptian tomato cultivar "Edkawy", three complementary approaches were used. These methods are amino acids analysis, gel electrophoresis, and Gas chromatography coupled with mass spectrometry (GC/MS). The results of the present study Show evidence of proteomic variations between both modified tomato and its non-modified counterpart. Amino acids concentrations, and the protein patterns separation on the 1D SDS-PAGE were not similar in the case of transformed tomato compared to that of the non-transformed counterpart. These detected differences are most likely derived from the process of transformation. Results also revealed that the efficiency of GC/MS approach to identify a mixture of unknown proteins is limited. GC/MS analysis was only able to identify few number of protein molecules. Therefore, more advanced and specific technologies like MALDI-TOF-MS are recommended to be employed.

Keywords: GMOs, unintended effects, proteomic variations, 1D SDS-PAGE, GC/MS

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Authors: M. Suresh Kumar, K. Ramani

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This paper proposed the harmonic elimination of Cascaded H-Bridge Multi-Level Inverter by using Selective Harmonic Elimination-Pulse Width Modulation method programmed with Particle Swarm Optimization algorithm. PSO method determine proficiently the required switching angles to eliminate low order harmonics up to the 11th order from the inverter output voltage waveform while keeping the magnitude of the fundamental harmonics at the desired value. Results demonstrate that the proposed method does efficiently eliminate a great number of specific harmonics and the output voltage is resulted in minimum Total Harmonic Distortion. The results shown that the PSO algorithm attain successfully to the global solution faster than other algorithms.

Keywords: multi-level inverter, Selective Harmonic Elimination Pulse Width Modulation (SHEPWM), Particle Swarm Optimization (PSO), Total Harmonic Distortion (THD)

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Authors: Fadwa Alaskar, Fang-Chieh Chou, Carlos Flores, Xiao-Yun Lu, Alexandre M. Bayen

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This article proposes a perception model for enhancing the accuracy and stability of car-following control of a longitudinally automated truck. We applied a fusion-based tracking algorithm on measurements of a single preceding vehicle needed for car-following control. This algorithm fuses two types of data, radar and LiDAR data, to obtain more accurate and robust longitudinal perception of the subject vehicle in various weather conditions. The filter’s resulting signals are fed to the gap control algorithm at every tracking loop composed by a high-level gap control and lower acceleration tracking system. Several highway tests have been performed with two trucks. The tests show accurate and fast tracking of the target, which impacts on the gap control loop positively. The experiments also show the fulfilment of control design requirements, such as fast speed variations tracking and robust time gap following.

Keywords: object tracking, perception, sensor fusion, adaptive cruise control, cooperative adaptive cruise control

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Authors: S. Sadallah

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In this paper, dynamic programming is used to determine the optimal management of financial resources in company. Solution of the problem by consider into simpler substructures is constructed. The optimal management of internal capital of company are simulated. The tools applied in this development are based on graph theory. The software of given problems is built by using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.

Keywords: management, software, optimal, greedy algorithm, graph-diagram

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Authors: Yemane Hailu Fissuh, Zhongzhan Zhang

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In biomedical researches and randomized clinical trials, the most commonly interested outcomes are time-to-event so-called survival data. The importance of robust models in this context is to compare the effect of randomly controlled experimental groups that have a sense of causality. Causal estimation is the scientific concept of comparing the pragmatic effect of treatments conditional to the given covariates rather than assessing the simple association of response and predictors. Hence, the causal effect based semiparametric transformation model was proposed to estimate the effect of treatment with the presence of possibly time-varying covariates. Due to its high flexibility and robustness, the semiparametric transformation model which shall be applied in this paper has been given much more attention for estimation of a causal effect in modeling left-truncated and right censored survival data. Despite its wide applications and popularity in estimating unknown parameters, the maximum likelihood estimation technique is quite complex and burdensome in estimating unknown parameters and unspecified transformation function in the presence of possibly time-varying covariates. Thus, to ease the complexity we proposed the modified estimating equations. After intuitive estimation procedures, the consistency and asymptotic properties of the estimators were derived and the characteristics of the estimators in the finite sample performance of the proposed model were illustrated via simulation studies and Stanford heart transplant real data example. To sum up the study, the bias of covariates was adjusted via estimating the density function for truncation variable which was also incorporated in the model as a covariate in order to relax the independence assumption of failure time and truncation time. Moreover, the expectation-maximization (EM) algorithm was described for the estimation of iterative unknown parameters and unspecified transformation function. In addition, the causal effect was derived by the ratio of the cumulative hazard function of active and passive experiments after adjusting for bias raised in the model due to the truncation variable.

Keywords: causal estimation, EM algorithm, semiparametric transformation models, time-to-event outcomes, time-varying covariate

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Authors: Muhammad Rafiullah Khan, Vanee Chonhenchob

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The effect of sodium alginate (1%) based edible coating incorporated natural essential oils; thymol, carvone and carvacrol as antimicrobial agents at different concentrations (0.1, 0.5 and 1.0 %) on the quality changes of fresh-cut pineapple were investigated. Pineapple dipped in distilled water was served as control. After coating, fruit were sealed in a modified atmosphere package (MAP) using high permeable film; and stored at 5 °C. Gas composition in package headspace, color values (L*, a*, b*, C*), TSS, pH, ethanol, browning, and microbial decay were monitored during storage. Oxygen concentration continuously decreased while carbon dioxide concentration inside all packages continuously increased over time. Color parameters (L*, b*, c*) decreased and a* values increased during storage. All essential oils significantly (p ≤ 0.05) prevented microbial growth than control. A significantly higher (p ≤ 0.05) ethanol content was found in the control than in all other treatments. Visible microbial growth, high ethanol, and low color values limited the shelf life to 6 days in control as compared to 9 days in all other treatments. Among all essential oils, thymol at all concentrations maintained the overall quality of the pineapple and could potentially be used commercially in fresh fruit industries for longer storage.

Keywords: essential oils, antibrowning agents, antimicrobial agents, modified atmosphere packaging, pineapple, microbial decay

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Authors: Muhammad Rafiullah Khan, Vanee Chonhenchob

Abstract:

The effect of sodium alginate (1%) based edible coating incorporated natural essential oils, thymol, carvone, and carvacrol as antimicrobial agents at different concentrations (0.1, 0.5, and 1.0%) on the quality changes of fresh-cut pineapple was investigated. Pineapple dipped in distilled water was served as control. After coating, the fruit was sealed in a modified atmosphere package (MAP) using high permeable film and stored at 5°C. Gas composition in package headspace, color values (L*, a*, b*, C*), TSS, pH, ethanol, browning, and microbial decay were monitored during storage. Oxygen concentration continuously decreased while carbon dioxide concentration inside all packages continuously increased over time. Color parameters (L*, b*, c*) decreased, and a* values increased during storage. All essential oils significantly (p ≤ 0.05) prevented microbial growth than control. A significantly higher (p ≤ 0.05) ethanol content was found in the control than in all other treatments. Visible microbial growth, high ethanol, and low color values limited the shelf life to 6 days in control as compared to 9 days in all other treatments. Among all essential oils, thymol at all concentrations maintained the overall quality of the pineapple and could potentially be used commercially in fresh fruit industries for longer storage.

Keywords: essential oils, antibrowning agents, antimicrobial agents, modified atmosphere packaging, microbial decay, pineapple

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Authors: Bo-Bin Xiaoa, Chia-Yi Liua

Abstract:

In the task of searching for anomalous radiation sources, personnel holding radiation detectors to search for radiation sources may be exposed to unnecessary radiation risk, and automated search using machines becomes a required project. The research uses various sophisticated algorithms, which are double Q learning, dueling network, and NoisyNet, of deep reinforcement learning to search for radiation sources. The simulation environment, which is a 10*10 grid and one shielding wall setting in it, improves the development of the AI model by training 1 million episodes. In each episode of training, the radiation source position, the radiation source intensity, agent position, shielding wall position, and shielding wall length are all set randomly. The three algorithms are applied to run AI model training in four environments where the training shielding wall is a full-shielding wall, a lead wall, a concrete wall, and a lead wall or a concrete wall appearing randomly. The 12 best performance AI models are selected by observing the reward value during the training period and are evaluated by comparing these AI models with the gradient search algorithm. The results show that the performance of the AI model, no matter which one algorithm, is far better than the gradient search algorithm. In addition, the simulation environment becomes more complex, the AI model which applied Double DQN combined Dueling and NosiyNet algorithm performs better.

Keywords: double Q learning, dueling network, NoisyNet, source searching

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Authors: Samiya Siddique, Taslima Akter Elma, Shahrina Mahzabin, Tamanna Jerin, Mohammed Russedul Islam

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In the maneuver and designing of highway engineering, pavement performance is a principal concern. Quality of construction and materials, traffic volume, climate, etc. are the factors that affect the performance of asphalt concrete. Modified asphalt requires to attain greater strength and stability even at inimical circumstances. In this point of view, pyrolytic carbon black (PCB), which is a by-product of waste tire pyrolysis, holds incomparable properties that individualizes it from other conventional fillers by making it an imminent modifier of bitumen. Optimum asphalt content of 60/70 penetration grade asphalt is determined 5% through the Marshall Stability and Flow test for the wearing course of flexible pavement. 5, 10, and 15 percentages of PCB are then used with neat asphalt for modification. Deviations of physical and rheological properties are investigated on both PCB modified and neat asphalt by going through several laboratory tests such as penetration, softening point, and ductility tests. The obtained results reveal that the performance of paving asphalt can be upgraded by modifying it with PCB. With the increasing percentage of PCB, ductility is gradually decreased, and also penetration grade is gradually reduced from 60/70 to 30/40. Furthermore, asphalt mixtures modified with PCB demonstrate higher stability and lower flow values. The research discloses that the apposite percentage of PCB used in asphalt concrete plays a significant role in the advancement of pavement performances and reutilizing of waste tires.

Keywords: asphalt modification, pavement performances, pyrolytic carbon black, marshall stability, wearing course

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Authors: Reza Rezaeipour Honarmandzad

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Wavelet analysis is an exciting method for solving difficult problems in mathematics, physics, and engineering, with modern applications as diverse as wave propagation, data compression, signal processing, image processing, pattern recognition, etc. Wavelets allow complex information such as signals, images and patterns to be decomposed into elementary forms at different positions and scales and subsequently reconstructed with high precision. In this paper a wavelet-based signal processing algorithm for airplane cable fault location is proposed. An orthogonal discrete wavelet decomposition and reconstruction algorithm is used to eliminate the noise in the aircraft cable fault signal. The experiment result has shown that the character of emission pulse and reflect pulse used to test the aircraft cable fault point are reserved and the high-frequency noise are eliminated by means of the proposed algorithm in this paper.

Keywords: wavelet analysis, signal processing, orthogonal discrete wavelet, noise, aircraft cable fault signal

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Authors: Yue-Tzu Yang, Peng-Jen Chen

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The present study deals with the numerical optimization of wavy channel with the help of genetic algorithm (GA). Three design variables related to the wave amplitude (A), the wavelength (λ) and the channel aspect ratio (α) are chosen and their ranges are decided through preliminary calculations of three-dimensional Navier-stokes and energy equations. A parametric study is also performed to show the effects of different design variables on the overall performance of the wavy channel. Objective functions related to the heat transfer and pressure drop, performance factor (PF) is formulated to analyze the performance of the wavy channel. The numerical results show that the wave amplitude and the channel aspect ratio have significant effects on the thermal performance. It can improve the performance of the wavy channels by increasing wave amplitude or decreasing the channel aspect ratio. Increasing wavelengths have no significant effects on the heat transfer performance.

Keywords: wavy channel, genetic algorithm, optimization, numerical simulation

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Authors: AnjalI A. Prasad

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Nowadays, social media played an important role in spreading misinformation or fake news. This study analyzes the fake news related to the COVID-19 pandemic spread in social media. This paper aims at evaluating and comparing different approaches that are used to mitigate this issue, including popular deep learning approaches, such as CNN, RNN, LSTM, and BERT algorithm for classification. To evaluate models’ performance, we used accuracy, precision, recall, and F1-score as the evaluation metrics. And finally, compare which algorithm shows better result among the four algorithms.

Keywords: BERT, CNN, LSTM, RNN

Procedia PDF Downloads 206

Authors: Suparman

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Piecewise polynomial regression model is very flexible model for modeling the data. If the piecewise polynomial regression model is matched against the data, its parameters are not generally known. This paper studies the parameter estimation problem of piecewise polynomial regression model. The method which is used to estimate the parameters of the piecewise polynomial regression model is Bayesian method. Unfortunately, the Bayes estimator cannot be found analytically. Reversible jump MCMC algorithm is proposed to solve this problem. Reversible jump MCMC algorithm generates the Markov chain that converges to the limit distribution of the posterior distribution of piecewise polynomial regression model parameter. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of piecewise polynomial regression model.

Keywords: piecewise regression, bayesian, reversible jump MCMC, segmentation

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Authors: Carlos Gonzalez

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When communicating using private and secure keys, there is always the doubt as to the identity of the message creator. We introduce an algorithm that uses the personal typing rhythm (keystroke dynamics) of the message originator to increase the trust of the authenticity of the message originator by the message recipient. The methodology proposes the use of a Rhythm Certificate Authority (RCA) to validate rhythm information. An illustrative example of the communication between Bob and Alice and the RCA is included. An algorithm of how to communicate with the RCA is presented. This RCA can be an independent authority or an enhanced Certificate Authority like the one used in public key infrastructure (PKI).

Keywords: authentication, digital signature, keystroke dynamics, personal rhythm, public-key encryption

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Authors: Hesham Abdin, Mohamed Zakaria, Talaat Abd-Elmonaem, Alaa El-Din Sayed Hafez

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Kalman filter algorithm is an estimator known as the workhorse of estimation. It has an important application in missile guidance, especially in lack of accurate data of the target due to noise or uncertainty. In this paper, a Kalman filter is used as a tracking filter in a simulated target-interceptor scenario with noise. It estimates the position, velocity, and acceleration of the target in the presence of noise. These estimations are needed for both proportional navigation and differential geometry guidance laws. A Kalman filter has a good performance at low noise, but a large noise causes considerable errors leads to performance degradation. Therefore, a new technique is required to overcome this defect using tuning factors to tune a Kalman filter to adapt increasing of noise. The values of the tuning factors are between 0.8 and 1.2, they have a specific value for the first half of range and a different value for the second half. they are multiplied by the estimated values. These factors have its optimum values and are altered with the change of the target heading. A genetic algorithm updates these selections to increase the maximum effective range which was previously reduced by noise. The results show that the selected factors have other benefits such as decreasing the minimum effective range that was increased earlier due to noise. In addition to, the selected factors decrease the miss distance for all ranges of this direction of the target, and expand the effective range which leads to increase probability of kill.

Keywords: proportional navigation, differential geometry, Kalman filter, genetic algorithm

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Authors: Karunambigai Mevani Govindasamy, Sathishkumar Ayyappan

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In this paper, we formulate the algorithm to find out the dominating function parameters of Intuitionistic Fuzzy Graphs(IFG). The methodology we adopted here is converting any physical problem into an IFG, and that has been transformed into Intuitionistic Fuzzy Matrix. Using Linear Program Solver software (LiPS), we found the defined parameters for the given IFG. We obtained these parameters for a path and cycle IFG. This study can be extended to other varieties of IFG. In particular, we obtain the definition of edge dominating function, minimal edge dominating function, fractional edge domination number (γ_if^') and upper fractional edge domination number (Γ_if^') of an intuitionistic fuzzy graph. Also, we formulated an algorithm which is appropriate to work on LiPS to find fractional edge domination number and upper fractional edge domination number of an IFG.

Keywords: fractional edge domination number, intuitionistic fuzzy cycle, intuitionistic fuzzy graph, intuitionistic fuzzy path

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Authors: Hamed Khani Arani, Mohammad Shariyat, Armaghan Mohammadian

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In the present study, the free vibration of magnetostrictive nano-plate (MsNP) resting on the Pasternak foundation is investigated. Firstly, the modified couple stress (MCS) and nonlocal elasticity theories are compared together and taken into account to consider the small scale effects; in this paper not only two theories are analyzed but also it improves the MCS theory is more accurate than nonlocal elasticity theory in such problems. A feedback control system is utilized to investigate the effects of a magnetic field. First-order shear deformation theory (FSDT), Hamilton’s principle and energy method are utilized in order to drive the equations of motion and these equations are solved by differential quadrature method (DQM) for simply supported boundary conditions. The MsNP undergoes in-plane forces in x and y directions. In this regard, the dimensionless frequency is plotted to study the effects of small scale parameter, magnetic field, aspect ratio, thickness ratio and compression and tension loads. Results indicate that these parameters play a key role on the natural frequency. According to the above results, MsNP can be used in the communications equipment, smart control vibration of nanostructure especially in sensor and actuators such as wireless linear micro motor and smart nano valves in injectors.

Keywords: feedback control system, magnetostrictive nano-plate, modified couple stress theory, nonlocal elasticity theory, vibration analysis

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: ring recognition, edge detection, X-ray computed tomography, dendrochronology

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