Search results for: number plate recognition

Authors: Pakinee Aimmanee, Phoom Chokratsamesiri

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Search engine has become an essential tool nowadays for people to search for their needed information on the internet. In this work, we evaluate the performance of the search engine from three factors: the keyword frequency, the number of inbound links, and the difficulty of the keyword. The evaluations are based on the ranking position and the number of days that Google has seen or detect the webpage. We find that the keyword frequency and the difficulty of the keyword do not affect the Google ranking where the number of inbound links gives remarkable improvement of the ranking position. The optimal number of inbound links found in the experiment is 10.

Keywords: SEO, information retrieval, web search, knowledge technologies

Procedia PDF Downloads 267

Authors: Tanveer Rasool, A. K. Dhiman

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The paper reports 2-D numerical study used to investigate the effect of changing working fluids with Prandtl numbers 0.71, 10 and 50 on the flow and convective heat transfer across an equilateral triangular cylinder placed in a horizontal channel with its apex facing the flow. Numerical results have been generated for fixed blockage ratio of 50% and for three Reynolds numbers of 50, 75, and 100 for each Prandtl numbers respectively. The studies show that for above range of Reynolds numbers, the overall drag coefficient is insensitive to the Prandtl number changes while as the heat transfer characteristics change drastically with changing Prandtl number of the working fluid. The results generated are in complete agreement with the previous literature available.

Keywords: Prandtl number, Reynolds number, drag coefficient, flow and isothermal patterns

Procedia PDF Downloads 376

Authors: Irina Veselova, Maria Makedonskaya, Olga Eremina, Alexandr Sidorov, Eugene Goodilin, Tatyana Shekhovtsova

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Such catecholamines as dopamine, norepinephrine, and epinephrine are the principal neurotransmitters in the sympathetic nervous system. Catecholamines and their metabolites are considered to be important markers of socially significant diseases such as atherosclerosis, diabetes, coronary heart disease, carcinogenesis, Alzheimer's and Parkinson's diseases. Currently, neurotransmitters can be studied via electrochemical and chromatographic techniques that allow their characterizing and quantification, although these techniques can only provide crude spatial information. Besides, the difficulty of catecholamine determination in biological materials is associated with their low normal concentrations (~ 1 nM) in biomaterials, which may become even one more order lower because of some disorders. In addition, in blood they are rapidly oxidized by monoaminooxidases from thrombocytes and, for this reason, the determination of neurotransmitter metabolism indicators in an organism should be very rapid (15—30 min), especially in critical states. Unfortunately, modern instrumental analysis does not offer a complex solution of this problem: despite its high sensitivity and selectivity, HPLC-MS cannot provide sufficiently rapid analysis, while enzymatic biosensors and immunoassays for the determination of the considered analytes lack sufficient sensitivity and reproducibility. Fluorescent and SERS-sensors remain a compelling technology for approaching the general problem of selective neurotransmitter detection. In recent years, a number of catecholamine sensors have been reported including RNA aptamers, fluorescent ribonucleopeptide (RNP) complexes, and boronic acid based synthetic receptors and the sensor operated in a turn-off mode. In this work we present the fluorescent and SERS turn-on sensor systems based on the bio- or chemorecognizing nanostructured films {chitosan/collagen-Tb/Eu/Cu-nanoparticles-indicator reagents} that provide the selective recognition, visualization, and sensing of the above mentioned catecholamines on the level of nanomolar concentrations in biomaterials (cell cultures, tissue etc.). We have (1) developed optically transparent porous films and gels of chitosan/collagen; (2) ensured functionalization of the surface by molecules-'recognizers' (by impregnation and immobilization of components of the indicator systems: biorecognizing and auxiliary reagents); (3) performed computer simulation for theoretical prediction and interpretation of some properties of the developed materials and obtained analytical signals in biomaterials. We are grateful for the financial support of this research from Russian Foundation for Basic Research (grants no. 15-03-05064 a, and 15-29-01330 ofi_m).

Keywords: biomaterials, fluorescent and SERS-recognition, neurotransmitters, solid-phase turn-on sensor system

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Authors: Om Prakash Keshri, Anand Kumar, Vinod K. Gupta

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In the present study, the effect of gravity modulation on the onset of convection in viscous fluid layer under the influence of induced magnetic field, salted from above on the boundaries, has been investigated. Linear and nonlinear stability analysis has been performed. A linear stability analysis is performed to show that the gravity modulation can significantly affect the stability limits of the system. A method based on small amplitude of the modulation is used to compute the critical value of Rayleigh number and wave number. The effect of Smith number, salute Rayleigh number and magnetic Prandtl number on the stability of the system is investigated.

Keywords: viscous fluid, induced magnetic field, gravity modulation, salute convection

Procedia PDF Downloads 176

Authors: Yehjune Heo

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Fingerprint Anti-Spoofing approaches have been actively developed and applied in real-world applications. One of the main problems for Fingerprint Anti-Spoofing is not robust to unseen samples, especially in real-world scenarios. A possible solution will be to generate artificial, but realistic fingerprint samples and use them for training in order to achieve good generalization. This paper contains experimental and comparative results with currently popular GAN based methods and uses realistic synthesis of fingerprints in training in order to increase the performance. Among various GAN models, the most popular StyleGAN is used for the experiments. The CNN models were first trained with the dataset that did not contain generated fake images and the accuracy along with the mean average error rate were recorded. Then, the fake generated images (fake images of live fingerprints and fake images of spoof fingerprints) were each combined with the original images (real images of live fingerprints and real images of spoof fingerprints), and various CNN models were trained. The best performances for each CNN model, trained with the dataset of generated fake images and each time the accuracy and the mean average error rate, were recorded. We observe that current GAN based approaches need significant improvements for the Anti-Spoofing performance, although the overall quality of the synthesized fingerprints seems to be reasonable. We include the analysis of this performance degradation, especially with a small number of samples. In addition, we suggest several approaches towards improved generalization with a small number of samples, by focusing on what GAN based approaches should learn and should not learn.

Keywords: anti-spoofing, CNN, fingerprint recognition, GAN

Procedia PDF Downloads 173

Authors: M. Yousaf, S. Usman

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The present study focused on the investigation of the effects of roughness elements on heat transfer during natural convection in a rectangular cavity using a numerical technique. Roughness elements were introduced on the bottom hot wall with a normalized amplitude (A*/H) of 0.1. Thermal and hydrodynamic behavior was studied using a computational method based on Lattice Boltzmann method (LBM). Numerical studies were performed for a laminar natural convection in the range of Rayleigh number (Ra) from 103 to 106 for a rectangular cavity of aspect ratio (L/H) 2 with a fluid of Prandtl number (Pr) 1.0. The presence of the sinusoidal roughness elements caused a minimum to the maximum decrease in the heat transfer as 7% to 17% respectively compared to the smooth enclosure. The results are presented for mean Nusselt number (Nu), isotherms, and streamlines.

Keywords: natural convection, Rayleigh number, surface roughness, Nusselt number, Lattice Boltzmann method

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Authors: Sara Hasani

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This research focuses on natural sudden onset disasters characterised as ‘occurring with little or no warning and often cause excessive injuries far surpassing the national response capacities’. Based on the panel analysis of the historic record of 4,252 natural onset disasters between 1980 to 2015, a predictive method was developed to predict the human impact of the disaster (fatality, injured, homeless) with less than 3% of errors. The geographical dispersion of the disasters includes every country where the data were available and cross-examined from various humanitarian sources. The records were then filtered into 4252 records of the disasters where the five predictive variables (disaster type, HDI, DRI, population, and population density) were clearly stated. The procedure was designed based on a combination of pattern recognition techniques and rule-based clustering for prediction and discrimination analysis to validate the results further. The result indicates that there is a relationship between the disaster human impact and the five socio-economic characteristics of the affected country mentioned above. As a result, a framework was put forward, which could predict the disaster’s human impact based on their severity rank in the early hours of disaster strike. The predictions in this model were outlined in two worst and best-case scenarios, which respectively inform the lower range and higher range of the prediction. A necessity to develop the predictive framework can be highlighted by noticing that despite the existing research in literature, a framework for predicting the human impact and estimating the needs at the time of the disaster is yet to be developed. This can further be used to allocate the resources at the response phase of the disaster where the data is scarce.

Keywords: disaster management, natural disaster, pattern recognition, prediction

Procedia PDF Downloads 138

Authors: Hong Im Shin

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Previous research demonstrated that self-objectification (women view themselves as objects for use) is related to system-justification. Three studies investigated whether cultural disposition as its system-justifying function could have an impact on self-objectification and dehumanization of sexualized women and men. Study 1 (N = 91) employed a survey methodology to examine the relationship between cultural disposition (collectivism vs. individualism), trait of system-justification, and self-objectification. The results showed that the higher tendency of collectivism was related to stronger system-justification and self-objectification. Study 2 (N = 60 females) introduced a single category implicit association task (SC-IAT) to assess the extent to which sexually objectified women were associated with uniquely human attributes (i.e., culture) compared to animal-related attributes (i.e., nature). According to results, female participants associated sexually objectified female targets less with human attributes compared to animal-related attributes. Study 3 (N = 46) investigated whether priming to individualism or collectivism was associated to system justification and sexual objectification of men and women with the use of a recognition task involving upright and inverted pictures of sexualized women and men. The results indicated that the female participants primed to individualism showed an inversion effect for sexualized women and men (person-like recognition), whereas there was no inversion effect for sexualized women in the priming condition of collectivism (object-like recognition). This implies that cultural disposition plays a mediating role for rationalizing the gender status, implicit dehumanization of sexualized females and self-objectification. Future research directions are discussed.

Keywords: cultural disposition, dehumanization, implicit test, self-objectification

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Authors: Ric Joseph R. Murillo, Edna N. Gueco, Dennis I. Merino

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Let F be C or R, where C and R are the set of complex numbers and real numbers, respectively, and n be a natural number. An n-by-n matrix A over the field F is called an α-involutory matrix or an α-involution if there exists an α in the field such that the square of the matrix is equal to αI, where I is the n-by-n identity matrix. If α is a complex number or a nonnegative real number, then an n-by-n matrix A over the field F can be written as a sum of n-by-n α-involutory matrices over the field F if and only if the trace of that matrix is an integral multiple of the square root of α. Meanwhile, if α is a negative real number, then a 2n-by-2n matrix A over R can be written as a sum of 2n-by-2n α-involutory matrices over R if and only the trace of the matrix is zero. Some other properties of α-involutory matrices are also determined

Keywords: α-involutory Matrices, sum of α-involutory Matrices, Trace, Matrix Theory

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Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

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Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: feature recognition, automation, sheet metal manufacturing, CAD, CAM

Procedia PDF Downloads 334

Authors: Rama Bhargava, Mania Goyal

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The problem of magnetohydrodynamics boundary layer flow and heat transfer on a permeable stretching surface in a second grade nanofluid under the effect of heat generation and partial slip is studied theoretically. The Brownian motion and thermophoresis effects are also considered. The boundary layer equations governed by the PDE’s are transformed into a set of ODE’s with the help of local similarity transformations. The differential equations are solved by variational finite element method. The effects of different controlling parameters on the flow field and heat transfer characteristics are examined. The numerical results for the dimensionless velocity, temperature and nanoparticle volume fraction as well as the reduced Nusselt and Sherwood number have been presented graphically. The comparison confirmed excellent agreement. The present study is of great interest in coating and suspensions, cooling of metallic plate, oils and grease, paper production, coal water or coal-oil slurries, heat exchangers technology, materials processing exploiting.

Keywords: viscoelastic nanofluid, partial slip, stretching sheet, heat generation/absorption, MHD flow, FEM

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Authors: Hadri Hussain, M.Nasir Ibrahim, Chee-Ming Ting, Mariani Idroas, Fuad Numan, Alias Mohd Noor

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A biometric security system has become an important application in client identification and verification system. A conventional biometric system is normally based on unimodal biometric that depends on either behavioural or physiological information for authentication purposes. The behavioural biometric depends on human body biometric signal (such as speech) and biosignal biometric (such as electrocardiogram (ECG) and phonocardiogram or heart sound (HS)). The speech signal is commonly used in a recognition system in biometric, while the ECG and the HS have been used to identify a person’s diseases uniquely related to its cluster. However, the conventional biometric system is liable to spoof attack that will affect the performance of the system. Therefore, a multimodal biometric security system is developed, which is based on biometric signal of ECG, HS, and speech. The biosignal data involved in the biometric system is initially segmented, with each segment Mel Frequency Cepstral Coefficients (MFCC) method is exploited for extracting the feature. The Hidden Markov Model (HMM) is used to model the client and to classify the unknown input with respect to the modal. The recognition system involved training and testing session that is known as client identification (CID). In this project, twenty clients are tested with the developed system. The best overall performance at 44 kHz was 93.92% for ECG and the worst overall performance was ECG at 88.47%. The results were compared to the best overall performance at 44 kHz for (20clients) to increment of clients, which was 90.00% for HS and the worst overall performance falls at ECG at 79.91%. It can be concluded that the difference multimodal biometric has a substantial effect on performance of the biometric system and with the increment of data, even with higher frequency sampling, the performance still decreased slightly as predicted.

Keywords: electrocardiogram, phonocardiogram, hidden markov model, mel frequency cepstral coeffiecients, client identification

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Authors: Azad Mohammed Ali Saber, Lanja Saeed Omer

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The present study deals with numerical method (FE) and experimental investigations on the vibration behavior of carbon fiber-polyester laminated plates. Finite element simulation is done using APDL (Ansys Parametric Design Language) macro codes software version 19. Solid185 layered structural element, including eight nodes, is adopted in this analysis. The experimental work is carried out using (Hand Layup method) to fabricate different layers and orientation angles of composite laminate plates. Symmetric samples include four layers (00/900)s and six layers (00/900/00)s, (00/00/900)s. Antisymmetric samples include one layer (00), (450), two layers (00/900), (-450/450), three layers (00/900/00), four layers (00/900)2, (-450/450)2, five layers (00/900)2.5, and six layers (00/900)3, (-450/450)3. An experimental investigation is carried out using a modal analysis technique with a Fast Fourier Transform Analyzer (FFT), Pulse platform, impact hammer, and accelerometer to obtain the frequency response functions. The influences of different parameters such as the number of layers, aspect ratio, modulus ratio, ply orientation, and different boundary conditions on the dynamic behavior of the CFRPs are studied, where the 1st, 2nd, and 3rd natural frequencies are observed to be the minimum for cantilever boundary condition (CFFF) and the maximum for full clamped boundary condition (CCCC). Experimental results show that the natural frequencies of laminated plates are significantly reliant on the type of boundary conditions due to the restraint effect at the edges. Good agreement is achieved among the finite element and experimental results. All results indicate that any increase in aspect ratio causes a decrease in the natural frequency of the CFRPs plate, while any increase in the modulus ratio or number of layers causes an increase in the fundamental natural frequency of vibration.

Keywords: vibration, composite materials, finite element, APDL ANSYS

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Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

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Authors: Kyung-Hoon Jang, Jae-Hyo Park, Kwang-Yeop Jang, Dongjin Kim

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The Tesla coil is an electrical resonant transformer circuit designed by inventor Nikola Tesla in 1891. It is used to produce high voltage, low current and high frequency alternating current electricity. Tesla experimented with a number of different configurations consisting of two or sometimes three coupled resonant electric circuits. This paper focuses on development and high voltage education to apply a Tesla coil to cuisine for high quality flavor and taste conditioning as well as high voltage education under 50 kV corona discharge. The result revealed that the velocity of roasted black belly pork by Tesla coil is faster than that of conventional methods such as hot grill and steel plate etc. depending on applied voltage level and applied voltage time. Besides, carbohydrate and crude protein increased, whereas natrium and saccharides significantly decreased after lightning surge by Tesla coil. This idea will be useful in high voltage education and high voltage application.

Keywords: corona discharge, Tesla coil, high voltage application, high voltage education

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Authors: Saad Alkentar, Abdulkareem Assalem

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Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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Authors: Masih Moore, Saeed Ziaei-Rad

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In this study, the stability characteristics of a bi-stable composite plate with different asymmetric composition are considered. The interest in bi-stable structures comes from their ability that these structures can have two different stable equilibrium configurations to define a discrete set of stable shapes. The structures can easily change the first stable shape to the second one by a simple snap action. The main purpose of the current research is to consider the effect of including resin layers on the stability characteristics of bi-stable laminates. To this end and In order to determine the magnitude of the loads that are responsible for snap through and snap back phenomena between two stable shapes of the laminate, a non-linear finite element method (FEM) is utilized. An experimental investigation was also carried out to study the critical loads that caused snapping between two different stable shapes. Several specimens were manufactured from T300/5208 graphite-epoxy with [0/90]T, [-30/60]T, [-20/70]T asymmetric stacking sequence. In order to create an accurate finite element model, different thickness of resin layers created during the manufacturing process of the laminate was measured and taken into account. The geometry of each lamina and the resin layers was characterized by optical microscopy from different locations of the laminates thickness. The exact thickness of each lamina and the resin layer in all specimens with [0/90]T,[-30/60]T, [-20/70]T stacking sequence were determined by using image processing technique.

Keywords: bi-stable laminates, finite element method, graphite-epoxy plate, snap behavior

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Authors: Agoston Restas

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Introduction: In case of managing disasters decision makers can face many times such a special situation where any pre-sign of the drastically change is missing therefore the improvised decision making can be required. The complexity, ambiguity, uncertainty or the volatility of the situation can require many times the improvisation as decision making. It can be taken at any level of the management (strategic, operational and tactical) but at tactical level the main reason of the improvisation is surely time pressure. It is certainly the biggest problem during the management. Methods: The author used different tools and methods to achieve his goals; one of them was the study of the relevant literature, the other one was his own experience as a firefighting manager. Other results come from two surveys that are referred to; one of them was an essay analysis, the second one was a word association test, specially created for the research. Results and discussion: This article proves that, in certain situations, the multi-criteria, evaluating decision-making processes simply cannot be used or only in a limited manner. However, it can be seen that managers, directors or commanders are many times in situations that simply cannot be ignored when making decisions which should be made in a short time. The functional background of decisions made in a short time, their mechanism, which is different from the conventional, was studied lately and this special decision procedure was given the name recognition-primed decision. In the article, author illustrates the limits of the possibilities of analytical decision-making, presents the general operating mechanism of recognition-primed decision-making, elaborates on its special model relevant to managers at tactical level, as well as explore and systemize the factors that facilitate (catalyze) the processes with an example with fire managers.

Keywords: decision making, disaster managers, recognition primed decision, model for making decisions in emergencies

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Authors: Dimakatso Machetele, Kowiyou Yessoufou

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Whilst several studies indicated that road accident events might be more complex than thought, we have a limited scientific understanding of this complexity in South Africa. The present project proposes and tests a more comprehensive metamodel that integrates multiple causality relationships among variables previously linked to road accidents. This was done by fitting a structural equation model (SEM) to the data collected from various sources. The study also fitted the GARCH Model (Generalized Auto-Regressive Conditional Heteroskedasticity) to predict the future of road accidents in the country. The analysis shows that the number of road accidents has been increasing since 1935. The road fatality rate follows a polynomial shape following the equation: y = -0.0114x²+1.2378x-2.2627 (R²=0.76) with y = death rate and x = year. This trend results in an average death rate of 23.14 deaths per 100,000 people. Furthermore, the analysis shows that the number of crashes could be significantly explained by the total number of vehicles (P < 0.001), number of registered vehicles (P < 0.001), number of unregistered vehicles (P = 0.003) and the population of the country (P < 0.001). As opposed to expectation, the number of driver licenses issued and total distance traveled by vehicles do not correlate significantly with the number of crashes (P > 0.05). Furthermore, the analysis reveals that the number of casualties could be linked significantly to the number of registered vehicles (P < 0.001) and total distance traveled by vehicles (P = 0.03). As for the number of fatal crashes, the analysis reveals that the total number of vehicles (P < 0.001), number of registered (P < 0.001) and unregistered vehicles (P < 0.001), the population of the country (P < 0.001) and the total distance traveled by vehicles (P < 0.001) correlate significantly with the number of fatal crashes. However, the number of casualties and again the number of driver licenses do not seem to determine the number of fatal crashes (P > 0.05). Finally, the number of crashes is predicted to be roughly constant overtime at 617,253 accidents for the next 10 years, with the worse scenario suggesting that this number may reach 1 896 667. The number of casualties was also predicted to be roughly constant at 93 531 overtime, although this number may reach 661 531 in the worst-case scenario. However, although the number of fatal crashes may decrease over time, it is forecasted to reach 11 241 fatal crashes within the next 10 years, with the worse scenario estimated at 19 034 within the same period. Finally, the number of fatalities is also predicted to be roughly constant at 14 739 but may also reach 172 784 in the worse scenario. Overall, the present study reveals the complexity of road accidents and allows us to propose several recommendations aimed to reduce the trend of road accidents, casualties, fatal crashes, and death in South Africa.

Keywords: road accidents, South Africa, statistical modelling, trends

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Authors: Saikiran Subbagari, Avinash Malladhi

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Anti Money Laundering (AML) regulations are designed to prevent money laundering and terrorist financing activities worldwide. Financial institutions around the world are legally obligated to identify, assess and mitigate the risks associated with money laundering and report any suspicious transactions to governing authorities. With increasing volumes of data to analyze, financial institutions seek to automate their AML processes. In the rise of financial crimes, optical character recognition (OCR), in combination with machine learning (ML) algorithms, serves as a crucial tool for automating AML processes by extracting the data from documents and identifying suspicious transactions. In this paper, we examine the utilization of OCR for AML and delve into various OCR techniques employed in AML processes. These techniques encompass template-based, feature-based, neural network-based, natural language processing (NLP), hidden markov models (HMMs), conditional random fields (CRFs), binarizations, pattern matching and stroke width transform (SWT). We evaluate each technique, discussing their strengths and constraints. Also, we emphasize on how OCR can improve the accuracy of customer identity verification by comparing the extracted text with the office of foreign assets control (OFAC) watchlist. We will also discuss how OCR helps to overcome language barriers in AML compliance. We also address the implementation challenges that OCR-based AML systems may face and offer recommendations for financial institutions based on the data from previous research studies, which illustrate the effectiveness of OCR-based AML.

Keywords: anti-money laundering, compliance, financial crimes, fraud detection, machine learning, optical character recognition

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Authors: Evy Van Puymbroeck, Wim Nagy, Ken Schotte, Heng Fang, Hans De Backer

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The knowledge of residual stresses for welded bridge components is essential to determine the effect of the residual stresses on the fatigue life behavior. The residual stresses of an orthotropic bridge deck are determined by simulating the welding process with finite element modelling. The stiffener is placed on top of the deck plate before welding. A chained thermal-mechanical analysis is set up to determine the distribution of residual stresses for the bridge deck. First, a thermal analysis is used to determine the temperatures of the orthotropic deck for different time steps during the welding process. Twin wire submerged arc welding is used to construct the orthotropic plate. A double ellipsoidal volume heat source model is used to describe the heat flow through a material for a moving heat source. The heat input is used to determine the heat flux which is applied as a thermal load during the thermal analysis. The heat flux for each element is calculated for different time steps to simulate the passage of the welding torch with the considered welding speed. This results in a time dependent heat flux that is applied as a thermal loading. Thermal material behavior is specified by assigning the properties of the material in function of the high temperatures during welding. Isotropic hardening behavior is included in the model. The thermal analysis simulates the heat introduced in the two plates of the orthotropic deck and calculates the temperatures during the welding process. After the calculation of the temperatures introduced during the welding process in the thermal analysis, a subsequent mechanical analysis is performed. For the boundary conditions of the mechanical analysis, the actual welding conditions are considered. Before welding, the stiffener is connected to the deck plate by using tack welds. These tack welds are implemented in the model. The deck plate is allowed to expand freely in an upwards direction while it rests on a firm and flat surface. This behavior is modelled by using grounded springs. Furthermore, symmetry points and lines are used to prevent the model to move freely in other directions. In the thermal analysis, a mechanical material model is used. The calculated temperatures during the thermal analysis are introduced during the mechanical analysis as a time dependent load. The connection of the elements of the two plates in the fusion zone is realized with a glued connection which is activated when the welding temperature is reached. The mechanical analysis results in a distribution of the residual stresses. The distribution of the residual stresses of the orthotropic bridge deck is compared with results from literature. Literature proposes uniform tensile yield stresses in the weld while the finite element modelling showed tensile yield stresses at a short distance from the weld root or the weld toe. The chained thermal-mechanical analysis results in a distribution of residual weld stresses for an orthotropic bridge deck. In future research, the effect of these residual stresses on the fatigue life behavior of welded bridge components can be studied.

Keywords: finite element modelling, residual stresses, thermal-mechanical analysis, welding simulation

Procedia PDF Downloads 159

Authors: Paweł Konieczka, Lech Raczyński, Wojciech Wiślicki, Oleksandr Fedoruk, Konrad Klimaszewski, Przemysław Kopka, Wojciech Krzemień, Roman Shopa, Jakub Baran, Aurélien Coussat, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Meysam Dadgar, Kamil Dulski, Aleksander Gajos, Beatrix C. Hiesmayr, Krzysztof Kacprzak, łukasz Kapłon, Grzegorz Korcyl, Tomasz Kozik, Deepak Kumar, Szymon Niedźwiecki, Dominik Panek, Szymon Parzych, Elena Pérez Del Río, Sushil Sharma, Shivani Shivani, Magdalena Skurzok, Ewa łucja Stępień, Faranak Tayefi, Paweł Moskal

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This paper develops the transformation of non-image data into 2-dimensional matrices, as a preparation stage for classification based on convolutional neural networks (CNNs). In positron emission tomography (PET) studies, CNN may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, much PET data still exists in non-image format and this fact opens a question on whether they can be used for training CNN. In this contribution, the main focus of this paper is the problem of processing vectors with a small number of features in comparison to the number of pixels in the output images. The proposed methodology was applied to the classification of PET coincidence events.

Keywords: convolutional neural network, kernel principal component analysis, medical imaging, positron emission tomography

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Authors: Ali Ulvi Uzer

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Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

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Authors: M. Iqbal Mahmud, Haeng Muk Cho, Seo Hyun Sang, Wang Wen Hai, Chang Heon Yi, Man Ik Hwang, Dae Hoon Kang

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Solenoid operated electromagnetic control valve (ECV) playing an important role for car’s air conditioning control system. ECV is used in external variable displacement swash plate type compressor and controls the entire air conditioning system by means of a pulse width modulation (PWM) input signal supplying from an external source (controller). Complete form of ECV contains number of internal features like valve body, core, valve guide, plunger, guide pin, plunger spring, bellows etc. While designing the ECV; dimensions of different internal items must meet the standard requirements as it is quite challenging. In this research paper, especially the dimensioning of ECV body and its three pressure ports through which the air/refrigerant passes are considered. Here internal leakage test analysis of ECV body is being carried out from its discharge port (Pd) to crankcase port (Pc) when the guide valve is placed inside it. The experiments have made both in ordinary and digital system using different assumptions and thereafter compare the results.

Keywords: electromagnetic control valve (ECV), leakage, pressure port, valve body, valve guide

Procedia PDF Downloads 388

Authors: Manutchanok Jongprasithporn, Rawiphorn Srivilai, Paweena Pongsopha

Abstract:

Fall is the most serious accident leading to increased unintentional injuries and mortality. Falls are not only the cause of suffering and functional impairments to the individuals, but also the cause of increasing medical cost and days away from work. The early detection of falls could be an advantage to reduce fall-related injuries and consequences of falls. Smartphones, embedded accelerometer, have become a common device in everyday life due to decreasing technology cost. This paper explores a physical activity monitoring and fall detection application in smartphones which is a non-invasive biomedical device to determine physical activities and fall event. The combination of application and sensors could perform as a biomedical sensor to monitor physical activities and recognize a fall. We have chosen Android-based smartphone in this study since android operating system is an open-source and no cost. Moreover, android phone users become a majority of Thai’s smartphone users. We developed Thai 3 Axis (TH3AX) as a physical activities and fall detection application which included command, manual, results in Thai language. The smartphone was attached to right hip of 10 young, healthy adult subjects (5 males, 5 females; aged< 35y) to collect accelerometer and gyroscope data during performing physical activities (e.g., walking, running, sitting, and lying down) and falling to determine threshold for each activity. Dependent variables are including accelerometer data (acceleration, peak acceleration, average resultant acceleration, and time between peak acceleration). A repeated measures ANOVA was performed to test whether there are any differences between DVs’ means. Statistical analyses were considered significant at p<0.05. After finding threshold, the results were used as training data for a predictive model of activity recognition. In the future, accuracies of activity recognition will be performed to assess the overall performance of the classifier. Moreover, to help improve the quality of life, our system will be implemented with patients and elderly people who need intensive care in hospitals and nursing homes in Thailand.

Keywords: activity recognition, accelerometer, fall, gyroscope, smartphone

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Authors: Jean-Pierre Lomaliza, Kwang-Seok Moon, Hanhoon Park

Abstract:

It is well-known that Ramer Douglas Peucker (RDP) algorithm greatly depends on the method of choosing starting points. Therefore, this paper focuses on finding such starting points that will optimize the results of RDP algorithm. Specifically, this paper proposes a curve approximation algorithm that finds flat points, called essential points, of an input curve, divides the curve into corner-like sub-curves using the essential points, and applies the RDP algorithm to the sub-curves. The number of essential points play a role on optimizing the approximation results by balancing the degree of shape information loss and the amount of data reduction. Through experiments with curves of various types and complexities of shape, we compared the performance of the proposed algorithm with three other methods, i.e., the RDP algorithm itself and its variants. As a result, the proposed algorithm outperformed the others in term of maintaining the original shapes of the input curve, which is important in various applications like pattern recognition.

Keywords: curve approximation, essential point, RDP algorithm

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Authors: Shatha A. Yousif, Hatem Jasim, Ali R. Abas, Dheya P. Yousef

Abstract:

To study the effect of the cross direction in bead wheat, three hybrid combinations (Babyle 113 , Iratome), (Sawa , Tamose2) and (Al Hashymya Al Iraq) were tested for plant height, number of tillers/m, number of grains per spike, weight of grains per spike, 1000-grain weight and grain yield. The results revealed that the direction of the cross had significant effect the number of grain/spike, tillers/m and grain yields. Grain yield was positively and significantly correlated with 1000-grain weight, number of grains per spike and tillers. Depend on the result of heritability and genetic advance it was suggested that 1000-grain weight number of grains per spike and tillers should be given emphasis for future wheat yield improvement programs.

Keywords: correlation, genetic advance, heritability, wheat, yield traits

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Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

Abstract:

Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: texture classification, texture descriptor, SIFT, SURF, ORB

Procedia PDF Downloads 349

Authors: Agustinus Rudatyo Himamunanto, Anastasia Rita Widiarti

Abstract:

Transliteration using Javanese manuscripts is one of methods to preserve and legate the wealth of literature in the past for the present generation in Indonesia. The transliteration manual process commonly requires philologists and takes a relatively long time. The automatic transliteration process is expected to shorten the time so as to help the works of philologists. The preprocessing and segmentation stage firstly done is used to manage the document images, thus obtaining image script units that will compile input document images free from noise and have the similarity in properties in the thickness, size, and slope. The next stage of characteristic extraction is used to find unique characteristics that will distinguish each Javanese script image. One of characteristics that is used in this research is the number of black pixels in each image units. Each image of Java scripts contained in the data training will undergo the same process similar to the input characters. The system testing was performed with the data of the book Hamong Tani. The book Hamong Tani was selected due to its content, age and number of pages. Those were considered sufficient as a model experimental input. Based on the results of random page automatic transliteration process testing, it was determined that the maximum percentage correctness obtained was 81.53%. The percentage of success was obtained in 32x32 pixel input image size with the 5x5 image window. With regard to the results, it can be concluded that the automatic transliteration model offered is relatively good.

Keywords: Javanese script, character recognition, statistical, automatic transliteration

Procedia PDF Downloads 326

Authors: Joo-Hyung Oh

Abstract:

The number of service users of 4G VoLTE (voice over LTE) using LTE data networks is rapidly growing. VoLTE based on all-IP network enables clearer and higher-quality voice calls than 3G. It does, however, pose new challenges; a voice call through IP networks makes it vulnerable to security threats such as wiretapping and forged or falsified information. And in particular, stealing other users’ phone numbers and forging or falsifying call request messages from outgoing voice calls within VoLTE result in considerable losses that include user billing and voice phishing to acquaintances. This paper focuses on the threats of caller phone number spoofing in the VoLTE and countermeasure technology as safety measures for mobile communication networks.

Keywords: LTE, 4G, VoLTE, phone number spoofing

Procedia PDF Downloads 414