Search results for: EM signals from material under load

Authors: A. Yacob, N. Hj. Ali, M. H. Yusoff, M. Y. MohdSaman, W. M. A. F. W. Hamzah

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Personalized learning becomes increasingly popular which not be restricted by time, place or any other barriers. This study proposes an analysis of Personalized Learning using Item Response Theory which considers course material difficulty and learner ability.The study investigates twenty undergraduate students at TATI University College, who are taking programming subject. By using the IRT,it was found that, finding the most appropriate problem levels to each student include high and low level test items together is not a problem. Thus, the student abilities can be asses more accurately and fairly. Learners who experience more anxiety will affect a heavier cognitive load and receive lower test scores.Instructors are encouraged to provide a supportive learning environment to enhance learning effectiveness because Cognitive Load Theory concerns the limited capacity of the brain to absorb new information.

Keywords: Analysis, Cognitive Load Theory, Item Response Theory, Learning, Motivation, Performance.

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Authors: J. M. Kim, K. H. Kwon

Abstract:

We show that in a two-channel sampling series expansion of band-pass signals, any finitely many missing samples can always be recovered via oversampling in a larger band-pass region. We also obtain an analogous result for multi-channel oversampling of harmonic signals.

Keywords: oversampling, multi-channel sampling, recovery of missing samples, band-pass signal, harmonic signal

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Authors: R. Sarathi, G. Nagesh, K. Vasudevan

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In the present work, an attempt has been made to understand the feasibility of using UHF technique for identification of any corona discharges/ arcing in insulating material due to water droplets. The sensors of broadband type are useful for identification of such discharges. It is realised that arcing initiated by liquid droplet radiates UHF signals in the entire bandwidth up to 2 GHz. The frequency content of the UHF signal generated due to corona/arcing is not much varied in epoxy nanocomposites with different weight percentage of clay content. The exfoliated/intercalated properties were analysed through TEM studies. It is realized that corona initiated discharges are of intermittent process. The hydrophobicity of the material characterized through contact angle measurement. It is realized that low Wt % of nanoclay content in epoxy resin reduces the surface carbonization due to arcing/corona discharges. The results of the study with gamma irradiated specimen indicates that contact angle, discharge inception time and evaporation time of the liquid are much lower than the virgin epoxy nanocomposite material.

Keywords: Arcing, Corona, epoxy resin, insulation, nanocomposites, UHF signal, water droplet.

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Authors: Jia-Rong Yeh, Tzu-Yu Lin, Jiann-Shing Shieh, Yun Chen

Abstract:

A mammal-s body can be seen as a blood vessel with complex tunnels. When heart pumps blood periodically, blood runs through blood vessels and rebounds from walls of blood vessels. Blood pressure signals can be measured with complex but periodic patterns. When an artery is clamped during a surgical operation, the spectrum of blood pressure signals will be different from that of normal situation. In this investigation, intestinal artery clamping operations were conducted to a pig for simulating the situation of intestinal blocking during a surgical operation. Similarity theory is a convenient and easy tool to prove that patterns of blood pressure signals of intestinal artery blocking and unblocking are surely different. And, the algorithm of Hilbert Huang Transform can be applied to extract the character parameters of blood pressure pattern. In conclusion, the patterns of blood pressure signals of two different situations, intestinal artery blocking and unblocking, can be distinguished by these character parameters defined in this paper.

Keywords: Blood pressure, spectrum, intestinal artery, similarity theory and Hilbert Huang Transform.

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Authors: N. Fuad, M. N. Taib, R. Jailani, M. E. Marwan

Abstract:

In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.

Keywords: Brain balancing, kNN, power spectral density, 3D EEG model.

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Authors: Mohammed Benbrahim, Khalid Benjelloun, Aomar Ibenbrahim, Adil Daoudi

Abstract:

The automatic classification of non stationary signals is an important practical goal in several domains. An essential classification task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present a modular system composed by three blocs: 1) Representation, 2) Dimensionality reduction and 3) Classification. The originality of our work consists in the use of a new wavelet called "Ben wavelet" in the representation stage. For the dimensionality reduction, we propose a new algorithm based on the random projection and the principal component analysis.

Keywords: Seismic signals, Ben Wavelet, Dimensionality reduction, Artificial neural networks, Classification.

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Authors: Olesya Bolkhovskaya, Alexey Davydov, Alexander Maltsev

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In this paper, approach to incoherent signal detection in multi-element antenna array are researched and modeled. Two types of useful signals with unknown wavefront were considered: first one, deterministic (Barker code), and second one, random (Gaussian distribution). The derivation of the sufficient statistics took into account the linearity of the antenna array. The performance characteristics and detecting curves are modeled and compared for different useful signals parameters and for different number of elements of the antenna array. Results of researches in case of some additional conditions can be applied to a digital communications systems.

Keywords: Antenna array, detection curves, performance characteristics, quadrature processing, signal detection.

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Authors: Redha Benzid, Farid Marir, Nour-Eddine Bouguechal

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This paper presents a new Quality-Controlled, wavelet based, compression method for electrocardiogram (ECG) signals. Initially, an ECG signal is decomposed using the wavelet transform. Then, the resulting coefficients are iteratively thresholded to guarantee that a predefined goal percent root mean square difference (GPRD) is matched within tolerable boundaries. The quantization strategy of extracted non-zero wavelet coefficients (NZWC), according to the combination of RLE, HUFFMAN and arithmetic encoding of the NZWC and a resulting look up table, allow the accomplishment of high compression ratios with good quality reconstructed signals.

Keywords: ECG compression, Non-uniform Max-Lloydquantizer, PRD, Quality-Controlled, Wavelet transform

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Authors: O. A. Rahmeh, P. Johnson, S. Lehmann

Abstract:

Grid networks provide the ability to perform higher throughput computing by taking advantage of many networked computer-s resources to solve large-scale computation problems. As the popularity of the Grid networks has increased, there is a need to efficiently distribute the load among the resources accessible on the network. In this paper, we present a stochastic network system that gives a distributed load-balancing scheme by generating almost regular networks. This network system is self-organized and depends only on local information for load distribution and resource discovery. The in-degree of each node is refers to its free resources, and job assignment and resource discovery processes required for load balancing is accomplished by using fitted random sampling. Simulation results show that the generated network system provides an effective, scalable, and reliable load-balancing scheme for the distributed resources accessible on Grid networks.

Keywords: Complex networks, grid networks, load-balancing, random sampling.

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Authors: Ephraim Gower, Thato Tsalaile, Monageng Kgwadi, Malcolm Hawksford.

Abstract:

In this paper, the statistical properties of filtered or convolved signals are considered by deriving the resulting density functions as well as the exact mean and variance expressions given a prior knowledge about the statistics of the individual signals in the filtering or convolution process. It is shown that the density function after linear convolution is a mixture density, where the number of density components is equal to the number of observations of the shortest signal. For circular convolution, the observed samples are characterized by a single density function, which is a sum of products.

Keywords: Circular Convolution, linear Convolution, mixture density function.

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Authors: S. M. Anowarul Haque, Md. Asiful Islam

Abstract:

Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: Load forecasting, artificial neural network, particle swarm optimization.

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Authors: Ž. Nikolić, H. Smoljanović, N. Živaljić

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This paper presents numerical model based on finite-discrete element method for analysis of the structural response of dry stone masonry structures under static and dynamic loads. More precisely, each discrete stone block is discretized by finite elements. Material non-linearity including fracture and fragmentation of discrete elements as well as cyclic behavior during dynamic load are considered through contact elements which are implemented within a finite element mesh. The application of the model was conducted on several examples of these structures. The performed analysis shows high accuracy of the numerical results in comparison with the experimental ones and demonstrates the potential of the finite-discrete element method for modelling of the response of dry stone masonry structures.

Keywords: Finite-discrete element method, dry stone masonry structures, static load, dynamic load.

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Authors: Z. Saidi, A.O. Boudraa, J.C. Cexus, S. Bourennane

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In this paper, a new time-delay estimation technique based on the cross IB-energy operator [5] is introduced. This quadratic energy detector measures how much a signal is present in another one. The location of the peak of the energy operator, corresponding to the maximum of interaction between the two signals, is the estimate of the delay. The method is a fully data-driven approach. The discrete version of the continuous-time form of the cross IBenergy operator, for its implementation, is presented. The effectiveness of the proposed method is demonstrated on real underwater acoustic signals arriving from targets and the results compared to the cross-correlation method.

Keywords: Teager-Kaiser energy operator, Cross-energyoperator, Time-Delay, Underwater acoustic signals.

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Authors: Jalal Karam, Raed Saad

Abstract:

This paper studies the effect of different compression constraints and schemes presented in a new and flexible paradigm to achieve high compression ratios and acceptable signal to noise ratios of Arabic speech signals. Compression parameters are computed for variable frame sizes of a level 5 to 7 Discrete Wavelet Transform (DWT) representation of the signals for different analyzing mother wavelet functions. Results are obtained and compared for Global threshold and level dependent threshold techniques. The results obtained also include comparisons with Signal to Noise Ratios, Peak Signal to Noise Ratios and Normalized Root Mean Square Error.

Keywords: Speech Compression, Wavelets.

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Authors: Anurag Jain, Rajneesh Kumar

Abstract:

Cloud computing is the outcome of rapid growth of internet. Due to elastic nature of cloud computing and unpredictable behavior of user, load balancing is the major issue in cloud computing paradigm. An efficient load balancing technique can improve the performance in terms of efficient resource utilization and higher customer satisfaction. Load balancing can be implemented through task scheduling, resource allocation and task migration. Various parameters to analyze the performance of load balancing approach are response time, cost, data processing time and throughput. This paper demonstrates a two level load balancer approach by combining join idle queue and join shortest queue approach. Authors have used cloud analyst simulator to test proposed two level load balancer approach. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.

Keywords: Cloud Analyst, Cloud Computing, Join Idle Queue, Join Shortest Queue, Load balancing, Task Scheduling.

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Authors: Sun-Ki Hong, Nam-HeeByeon, Jung-Seop Lee, Tae-Sam Kang

Abstract:

For Common R or R-L load to apply arbitrary voltage, the bridge traditional inverters don’t have any difficulties by PWM method. However for driving some piezoelectric actuator, arbitrary voltage not a pulse but a steady voltage should be applied. Piezoelectric load is considered as R-C load and its voltage does not decrease even though the applied voltage decreases. Therefore it needs some special inverter with circuit that can discharge the capacitive energy. Especially for unidirectional arbitrary voltage driving like as sine wave, it becomes more difficult problem. In this paper, a charge and discharge circuit for unidirectional arbitrary voltage driving for piezoelectric actuator is proposed. The circuit has charging and discharging switches for increasing and decreasing output voltage. With the proposed simple circuit, the load voltage can have any unidirectional level with tens of bandwidth because the load voltage can be adjusted by switching the charging and discharging switch appropriately. The appropriateness is proved from the simulation of the proposed circuit.

Keywords: DC-DC converter, analog output voltage, sinusoidal drive, piezoelectric load, discharging circuit.

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Authors: L. Bikulciene, E. Venskaityte, G. Jarusevicius

Abstract:

Nonstationary and nonlinear signals generated by living complex systems defy traditional mechanistic approaches, which are based on homeostasis. Previous our studies have shown that the evaluation of the interactions of physiological signals by using special analysis methods is suitable for observation of physiological processes. It is demonstrated the possibility of using deep physiological model, based on the interpretation of the changes of the human body’s functional states combined with an application of the analytical method based on matrix theory for the physiological signals analysis, which was applied on high risk cardiac patients. It is shown that evaluation of cardiac signals interactions show peculiar for each individual functional changes at the onset of hemodynamic restoration procedure. Therefore, we suggest that the alterations of functional state of the body, after patients overcome surgery can be complemented by the data received from the suggested approach of the evaluation of functional variables’ interactions.

Keywords: Cardiac diseases, Complex systems theory, ECG analysis, matrix analysis.

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Authors: Aleš Florian, Lenka Ševelová

Abstract:

Low volume roads are widely used all over the world. To improve their quality the computer simulation of their behavior is proposed. The FEM model enables to determine stress and displacement conditions in the pavement and/or also in the particular material layers. Different variants of pavement layers, material used, humidity as well as loading conditions can be studied. Among others, the input information about material properties of individual layers made from recycled materials is crucial for obtaining results as exact as possible. For this purpose the cyclic-load triaxial test machine testing of cyclic-load performance of materials is a promising test method. The test is able to simulate the real traffic loading on particular materials taking into account the changes in the horizontal stress conditions produced in particular layers by crossings of vehicles. Also the test specimen can be prepared with different amount of water. Thus modulus of elasticity (Young modulus) of different materials including recycled ones can be measured under the different conditions of horizontal and vertical stresses as well as under the different humidity conditions. Using the proposed testing procedure the modulus of elasticity of recycled materials used in the newly built low volume road is obtained under different stress and humidity conditions set to standard, dry and fully saturated level. Obtained values of modulus of elasticity are used in FEA.

Keywords: FEA, FEM, geotechnical materials, low volume roads, pavement, triaxial test, Young modulus.

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Authors: Dia I. Abu-Al-Nadi, M. J. Mismar, T. H. Ismail

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A technique for estimating the direction-of-arrival (DOA) of unknown number of source signals is presented using the eigen-approach. The eigenvector corresponding to the minimum eigenvalue of the autocorrelation matrix yields the minimum output power of the array. Also, the array polynomial with this eigenvector possesses roots on the unit circle. Therefore, the pseudo-spectrum is found by perturbing the phases of the roots one by one and calculating the corresponding array output power. The results indicate that the DOAs and the number of source signals are estimated accurately in the presence of a wide range of input noise levels.

Keywords: Array signal processing, direction-of-arrival, antenna arrays, eigenvalues, eigenvectors.

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Authors: Ayaz Keerio, Bhargav Kumar Mitra, Philip Birch, Rupert Young, Chris Chatwin

Abstract:

Preprocessing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. In this paper, we present some popular statistical outlier-detection based strategies to segregate the silence/unvoiced part of the speech signal from the voiced portion. The proposed methods are based on the utilization of the 3 σ edit rule, and the Hampel Identifier which are compared with the conventional techniques: (i) short-time energy (STE) based methods, and (ii) distribution based methods. The results obtained after applying the proposed strategies on some test voice signals are encouraging.

Keywords: STE based methods, Mahalanobis distance, 3 edit σ rule, Hampel Identifier.

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Authors: Yueming Wang, Zenghui Zhang, Rendong Ying, Peilin Liu

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Sparse representation has long been studied and several dictionary learning methods have been proposed. The dictionary learning methods are widely used because they are adaptive. In this paper, a new dictionary learning method for audio is proposed. Signals are at first decomposed into different degrees of Intrinsic Mode Functions (IMF) using Empirical Mode Decomposition (EMD) technique. Then these IMFs form a learned dictionary. To reduce the size of the dictionary, the K-means method is applied to the dictionary to generate a K-EMD dictionary. Compared to K-SVD algorithm, the K-EMD dictionary decomposes audio signals into structured components, thus the sparsity of the representation is increased by 34.4% and the SNR of the recovered audio signals is increased by 20.9%.

Keywords: Dictionary Learning, EMD, K-means Method, Sparse Representation.

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Authors: Tatsuya Sakoda, Yuta Nakamura, Junichiro Kitajima, Masaki Sugiura, Satoshi Kurihara, Kenji Baba, Koichiro Kaneko, Takayoshi Yarimitsu

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An acoustic emission (AE) technique is useful for detection of partial discharges (PDs) at a joint and a terminal section of a cross-linked polyethylene (XLPE) cable. For AE technique, it is not difficult to detect a PD using AE sensors. However, it is difficult to grasp whether the detected AE signal is owing to a single discharge or not. Additionally, when an AE technique is applied at a terminal section of a XLPE cable in salt pollution district, for example, there is possibility of detection of AE signals owing to creeping discharges on the surface of electric power apparatus. In this study, we evaluated AE signals in order to grasp what kind of information we can get from detected AE signals. The results showed that envelop detection of AE signal and a period which some AE signals were continuously detected were good indexes for estimating state-of-discharge.

Keywords: acoustic emission, creeping discharge, partial discharge, XLPE cable

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Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasy

Abstract:

Energy consumption schedule (ECS) technique shifts usage of loads from on peak hours and redistributes them throughout the day according to residents’ operating time preferences. This technique is used as form of indirect control from utility to improve the load curve and hence its load factor and reduce customer’s total electric bill as well. Similarly, load shifting technique achieves ECS purposes but as direct control form applied from utility. In this paper, ECS is simulated twice as optimal constrained mathematical formula, solved by using CVX program in MATLAB^® R2013b. First, it is utilized for single residential building with ten apartments to determine max allowable energy consumption per hour for each residential apartment. Then, it is used for single apartment with number of shiftable domestic devices, where operating schedule is deduced using previous simulation output results as constraints. The paper ends by giving differences between ECS technique and load shifting technique via literature and simulation. Based on results assessment, it will be shown whether using ECS or load shifting is more beneficial to both customer and utility.

Keywords: Energy consumption schedule, load shifting technique, comparison.

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Authors: Mohammed S. Al-Ansari

Abstract:

This paper presents an analytical model to estimate the cost of an optimized design of reinforced concrete isolated footing base on structural safety. Flexural and optimized formulas for square and rectangular footingare derived base on ACI building code of design, material cost and optimization. The optimization constraints consist of upper and lower limits of depth and area of steel. Footing depth and area of reinforcing steel are to be minimized to yield the optimal footing dimensions. Optimized footing materials cost of concrete, reinforcing steel and formwork of the designed sections are computed. Total cost factor TCF and other cost factors are developed to generalize and simplify the calculations of footing material cost. Numerical examples are presented to illustrate the model capability of estimating the material cost of the footing for a desired axial load.

Keywords: Footing, Depth, Concrete, Steel, Formwork, Optimization, Material cost, Cost Factors.

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Authors: Jairo Aparecido Martins, Estaner Claro Romão

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This paper presents the static and cyclic stresses in combination with fatigue analysis resultant of loads applied on the friction discs usually utilized on industrial clutches. The material chosen to simulate the friction discs under load is aluminum. The numerical simulation was done by software COMSOL^TM Multiphysics. The results obtained for static loads showed enough stiffness for both geometries and the material utilized. On the other hand, in the fatigue standpoint, failure is clearly verified, what demonstrates the importance of both approaches, mainly dynamical analysis. The results and the conclusion are based on the stresses on disc, counted stress cycles, and fatigue usage factor.

Keywords: Aluminum, industrial clutch, static and dynamic loading, numerical simulation.

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Authors: Palak J. Shukla, Atul K. Desai, Chentankumar D. Modhera

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For any country in the world, it has become a priority to protect the critical infrastructure from looming risks of terrorism. In any infrastructure system, the structural elements like lower floors, exterior columns, walls etc. are key elements which are the most susceptible to damage due to blast load. The present study revisits the state of art review of the design and analysis of reinforced concrete panels subjected to blast loading. Various aspects in association with blast loading on structure, i.e. estimation of blast load, experimental works carried out previously, the numerical simulation tools, various material models, etc. are considered for exploring the current practices adopted worldwide. Discussion on various parametric studies to investigate the effect of reinforcement ratios, thickness of slab, different charge weight and standoff distance is also made. It was observed that for the simulation of blast load, CONWEP blast function or equivalent numerical equations were successfully employed by many researchers. The study of literature indicates that the researches were carried out using experimental works and numerical simulation using well known generalized finite element methods, i.e. LS-DYNA, ABAQUS, AUTODYN. Many researchers recommended to use concrete damage model to represent concrete and plastic kinematic material model to represent steel under action of blast loads for most of the numerical simulations. Most of the studies reveal that the increase reinforcement ratio, thickness of slab, standoff distance was resulted in better blast resistance performance of reinforced concrete panel. The study summarizes the various research results and appends the present state of knowledge for the structures exposed to blast loading.

Keywords: Blast phenomenon, experimental methods, material models, numerical methods.

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Authors: Kent Salomonsson, Xuefang Zhao, Sara Kallin

Abstract:

Human soft tissue is loaded and deformed by any activity, an effect known as a stress-strain relationship, and is often described by a load and tissue elongation curve. Several advances have been made in the fields of biology and mechanics of soft human tissue. However, there is limited information available on in vivo tissue mechanical characteristics and behavior. Confident mechanical properties of human soft tissue cannot be extrapolated from e.g. animal testing. Thus, there is need for non invasive methods to analyze mechanical characteristics of soft human tissue. In the present study, the internal mechanical conditions of the lower limb, which is subject to an external load, is studied by use of the finite element method. A detailed finite element model of the lower limb is made possible by use of MRI scans. Skin, fat, bones, fascia and muscles are represented separately and the material properties for them are obtained from literature. Previous studies have been shown to address macroscopic deformation features, e.g. indentation depth, to a large extent. However, the detail in which the internal anatomical features have been modeled does not reveal the critical internal strains that may induce hypoxia and/or eventual tissue damage. The results of the present study reveals that lumped material models, i.e. averaging of the material properties for the different constituents, does not capture regions of critical strains in contrast to more detailed models.

Keywords: FEM, human soft tissue, indentation, properties.

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Authors: Nebi Gedik

Abstract:

The goal of motor image brain computer interface research is to create a link between the central nervous system and a computer or device. The most important signal for brain-computer interface is the electroencephalogram. The aim of this research is to explore a set of effective features from EEG signals, separated into frequency bands, using wave atom sub-bands to discriminate right and left-hand motor imagery signals. Over the transform coefficients, feature vectors are constructed for each frequency range and each transform sub-band, and their classification performances are tested. The method is validated using EEG signals from the BCI competition III dataset IIIa and classifiers such as support vector machine and k-nearest neighbors.

Keywords: motor imagery, EEG, Wave atom transform sub-bands, SVM, k-NN

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Authors: A. B. Chehreh, M. Grätzel, M. Klein, J. P. Bergmann, F. Walther

Abstract:

Friction stir welding (FSW) is an advantageous method in the thermal joining processes, featuring the welding of various dissimilar and similar material combinations, joining temperatures below the melting point which prevents irregularities such as pores and hot cracks as well as high strengths mechanical joints near the base material. The FSW process consists of a rotating tool which is made of a shoulder and a probe. The welding process is based on a rotating tool which plunges in the workpiece under axial pressure. As a result, the material is plasticized by frictional heat which leads to a decrease in the flow stress. During the welding procedure, the material is continuously displaced by the tool, creating a firmly bonded weld seam behind the tool. However, the mechanical properties of the weld seam are affected by the design and geometry of the tool. These include in particular microstructural and surface properties which can favor crack initiation. Following investigation compares the dynamic properties of FSW weld seams with conventional and stationary shoulder geometry based on load increase test (LIT). Compared to classical Woehler tests, it is possible to determine the fatigue strength of the specimens after a short amount of time. The investigations were carried out on a robotized welding setup on 2 mm thick EN AW 5754 aluminum alloy sheets. It was shown that an increased tensile and fatigue strength can be achieved by using the stationary shoulder concept. Furthermore, it could be demonstrated that the LIT is a valid method to describe the fatigue behavior of FSW weld seams.

Keywords: Aluminum alloy, fatigue performance, fracture, friction stir welding.

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Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

Abstract:

In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: Fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange.

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