Search results for: Inverse DiscreteCosine Transform (IDCT)

Authors: Y. J. Zhou, G. Lu

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In this paper, an analytical study is made for the dynamic behavior of human brain tissue under transient loading. In this analytical model the Mooney-Rivlin constitutive law is coupled with visco-elastic constitutive equations to take into account both the nonlinear and time-dependent mechanical behavior of brain tissue. Five ordinary differential equations representing the relationships of five main parameters (radial stress, circumferential stress, radial strain, circumferential strain, and particle velocity) are obtained by using the characteristic method to transform five partial differential equations (two continuity equations, one motion equation, and two constitutive equations). Analytical expressions of the attenuation properties for spherical wave in brain tissue are analytically derived. Numerical results are obtained based on the five ordinary differential equations. The mechanical responses (particle velocity and stress) of brain are compared at different radii including 5, 6, 10, 15 and 25 mm under four different input conditions. The results illustrate that loading curves types of the particle velocity significantly influences the stress in brain tissue. The understanding of the influence by the input loading cures can be used to reduce the potentially injury to brain under head impact by designing protective structures to control the loading curves types.

Keywords: Analytical method, mechanical responses, spherical wave propagation, traumatic brain injury.

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Authors: Mustafa M. Donma, Orkide Donma

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Zinc (Zn) is a vital element required for growth and development particularly in children. It exhibits some protective effects against cardiovascular diseases (CVDs). Zn may be a potential biomarker of cardiovascular health. High sensitive cardiac troponin T (hs-cTnT) and cardiac myosin binding protein C (cMyBP-C) are new generation markers used for prediagnosis, diagnosis and prognosis of CVDs. The aim of this study is to determine Zn as well as new generation cardiac markers’ profiles in children with normal body mass index (N-BMI), obese (OB), morbid obese (MO) children and children with metabolic syndrome (MetS) findings. The association among them will also be investigated. Four study groups were constituted. The study protocol was approved by the institutional Ethics Committee of Tekirdag Namik Kemal University. Parents of the participants filled informed consent forms to participate in the study. Group 1 is composed of 44 children with N-BMI. Group 2 and Group 3 comprised 43 OB and 45 MO children, respectively. 45 MO children with MetS findings were included in Group 4. World Health Organization age- and sex-adjusted BMI percentile tables were used to constitute groups. These values were 15-85, 95-99 and above 99 for N-BMI, OB and MO, respectively. Criteria for MetS findings were determined. Routine biochemical analyses including Zn were performed. hs-cTnT and cMyBP-C concentrations were measured by enzyme-linked immunosorbent assay. Data were analyzed by using SPSS software. p < 0.05 was accepted as significant. Four groups were matched for age and gender. Decreased Zn concentrations were measured in Groups 2, 3 and 4 compared to Group 1. Groups did not differ from one another in terms of hs-cTnT. There were statistically significant differences between cMyBP-C levels of MetS group and N-BMI as well as OB groups. There was an increasing trend going from N-BMI group to MetS group. There were statistically significant negative correlations between Zn and hs-cTnT as well as cMyBP-C concentrations in MetS group. In conclusion, inverse correlations detected between Zn and new generation cardiac markers (hs-TnT and cMyBP-C) have pointed out that decreased levels of Zn accompany increased levels of hs-cTnT as well as cMyBP-C in children with MetS. This finding emphasizes that both Zn and these new generation cardiac markers may be evaluated as biomarkers of cardiovascular health during severe childhood obesity precipitated with MetS findings and also suggested as the messengers of the future risk in the adulthood periods of children with MetS.

Keywords: Cardiac myosin binding protein-C, cardiovascular diseases, children, high sensitive cardiac troponin T, obesity.

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Authors: Abed Sami Qawasme, Sameer Khader

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This paper describes the effects of photovoltaic voltage changes on Multi-level inverter (MLI) due to solar irradiation variations, and methods to overcome these changes. The irradiation variation affects the generated voltage, which in turn varies the switching angles required to turn-on the inverter power switches in order to obtain minimum harmonic content in the output voltage profile. Genetic Algorithm (GA) is used to solve harmonics elimination equations of eleven level inverters with equal and non-equal dc sources. After that artificial neural network (ANN) algorithm is proposed to generate appropriate set of switching angles for MLI at any level of input dc sources voltage causing minimization of the total harmonic distortion (THD) to an acceptable limit. MATLAB/Simulink platform is used as a simulation tool and Fast Fourier Transform (FFT) analyses are carried out for output voltage profile to verify the reliability and accuracy of the applied technique for controlling the MLI harmonic distortion. According to the simulation results, the obtained THD for equal dc source is 9.38%, while for variable or unequal dc sources it varies between 10.26% and 12.93% as the input dc voltage varies between 4.47V nd 11.43V respectively. The proposed ANN algorithm provides satisfied simulation results that match with results obtained by alternative algorithms.

Keywords: Multi level inverter, genetic algorithm, artificial neural network, total harmonic distortion.

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Authors: Nan-Chyuan Tsai, Chao-Wen Chiang, Bai-Lu Wang

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The three-time-scale plant model of a wind power generator, including a wind turbine, a flexible vertical shaft, a Variable Inertia Flywheel (VIF) module, an Active Magnetic Bearing (AMB) unit and the applied wind sequence, is constructed. In order to make the wind power generator be still able to operate as the spindle speed exceeds its rated speed, the VIF is equipped so that the spindle speed can be appropriately slowed down once any stronger wind field is exerted. To prevent any potential damage due to collision by shaft against conventional bearings, the AMB unit is proposed to regulate the shaft position deviation. By singular perturbation order-reduction technique, a lower-order plant model can be established for the synthesis of feedback controller. Two major system parameter uncertainties, an additive uncertainty and a multiplicative uncertainty, are constituted by the wind turbine and the VIF respectively. Frequency Shaping Sliding Mode Control (FSSMC) loop is proposed to account for these uncertainties and suppress the unmodeled higher-order plant dynamics. At last, the efficacy of the FSSMC is verified by intensive computer and experimental simulations for regulation on position deviation of the shaft and counter-balance of unpredictable wind disturbance.

Keywords: Sliding Mode Control, Singular Perturbation, Variable Inertia Flywheel.

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Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

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Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: Optimal control, ensemble Kalman Filter, topography reconstruction, data assimilation, shallow water equations.

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Authors: Rajesh Kumar, Puneet Aggarwal

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In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied.

Keywords: Block rotor test, DC test, no-load test, virtual environment, VSI.

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Authors: Muhammad R. Islam, Mohammad Dalour H. Beg, Saidatul S. Jamari

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Considering palm oil as non-drying oil owing to its low iodine value, an attempt was taken to increase the unsaturation in the fatty acid chains of palm oil for the preparation of alkyds. To increase the unsaturation in the palm oil, sulphuric acid (SA) and para-toluene sulphonic acid (PTSA) was used prior to alcoholysis for the dehydration process. The iodine number of the oil samples was checked for the unsaturation measurement by Wijs method. Alkyd resin was prepared using the dehydrated palm oil by following alcoholysis and esterification reaction. To improve the film properties 0.5wt.% multi-wall carbon nano tubes (MWCNTs) were used to manufacture polymeric film. The properties of the resins were characterized by various physico-chemical properties such as density, viscosity, iodine value, saponification value, etc. Structural elucidation was confirmed by Fourier transform of infrared spectroscopy and proton nuclear magnetic resonance; surfaces of the films were examined by field-emission scanning electron microscope. In addition, pencil hardness and chemical resistivity was also measured by using standard methods. The effect of enhancement of the unsaturation in the fatty acid chain found significant and motivational. The resin prepared with dehydrated palm oil showed improved properties regarding hardness and chemical resistivity testing. The incorporation of MWCNTs enhanced the thermal stability and hardness of the films as well.

Keywords: Alkyd resin, nano-coatings, dehydration, palm oil.

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Authors: Christian Arcos, Marley Vellasco, Abraham Alcaim

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In this paper, we present a wavelet coefficients masking based on Local Binary Patterns (WLBP) approach to enhance the temporal spectra of the wavelet coefficients for speech enhancement. This technique exploits the wavelet denoising scheme, which splits the degraded speech into pyramidal subband components and extracts frequency information without losing temporal information. Speech enhancement in each high-frequency subband is performed by binary labels through the local binary pattern masking that encodes the ratio between the original value of each coefficient and the values of the neighbour coefficients. This approach enhances the high-frequency spectra of the wavelet transform instead of eliminating them through a threshold. A comparative analysis is carried out with conventional speech enhancement algorithms, demonstrating that the proposed technique achieves significant improvements in terms of PESQ, an international recommendation of objective measure for estimating subjective speech quality. Informal listening tests also show that the proposed method in an acoustic context improves the quality of speech, avoiding the annoying musical noise present in other speech enhancement techniques. Experimental results obtained with a DNN based speech recognizer in noisy environments corroborate the superiority of the proposed scheme in the robust speech recognition scenario.

Keywords: Binary labels, local binary patterns, mask, wavelet coefficients, speech enhancement, speech recognition.

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Authors: Ruchi Vyas, Sanjay Singh, Rashmi Sisodia

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Chlorophytum borivillianum root extract (CBE) was chosen as a reducing agent to fabricate silver nanoparticles with the aim of studying its radioprotective efficacy. The formation of synthesized nanoparticles was characterized by UV–visible analysis (UV–vis), Fourier transform infra-red (FT-IR), Transmission electron microscopy (TEM), Scanning electron microscope (SEM). TEM analysis showed particles size in the range of 20-30 nm. For this study, Swiss albino mice were selected from inbred colony and were divided into 4 groups: group I- control (irradiated-6 Gy), group II- normal (vehicle treated), group III- plant extract alone and group IV- CB-AgNPs (dose of 50 mg/kg body wt./day) administered orally for 7 consecutive days before irradiation to serve as experimental. CB-AgNPs pretreatment rendered significant increase in body weight and testes weight at various post irradiation intervals in comparison to irradiated group. Supplementation of CB-AgNPs reversed the adverse effects of gamma radiation on biochemical parameters as it notably ameliorated the elevation in lipid peroxidation and decline in glutathione concentration in testes. These observations indicate the radio-protective potential of CB-AgNPs in testicular constituents against gamma irradiation in mice.

Keywords: Chlorophytum borivillianum, gamma radiation, radioprotective, silver nanoparticles.

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Authors: Jason Chien-Hsun Tseng, Nguyen Dong-Thai Dao, Chong-Ching Chang

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A novel PDE solver using the multidimensional wave digital filtering (MDWDF) technique to achieve the solution of a 2D seismic wave system is presented. In essence, the continuous physical system served by a linear Kirchhoff circuit is transformed to an equivalent discrete dynamic system implemented by a MD wave digital filtering (MDWDF) circuit. This amounts to numerically approximating the differential equations used to describe elements of a MD passive electronic circuit by a grid-based difference equations implemented by the so-called state quantities within the passive MDWDF circuit. So the digital model can track the wave field on a dense 3D grid of points. Details about how to transform the continuous system into a desired discrete passive system are addressed. In addition, initial and boundary conditions are properly embedded into the MDWDF circuit in terms of state quantities. Graphic results have clearly demonstrated some physical effects of seismic wave (P-wave and S–wave) propagation including radiation, reflection, and refraction from and across the hard boundaries. Comparison between the MDWDF technique and the finite difference time domain (FDTD) approach is also made in terms of the computational efficiency.

Keywords: Seismic Wave Propagation, Multi-dimension WaveDigital Filters, Partial Differential Equations.

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Authors: Guanqiao Wang, Hongyang Yu

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There is a lot of repetitive work in the traditional construction industry. These repetitive tasks can significantly improve production efficiency by replacing manual tasks with robots. Therefore, robots appear more and more frequently in the construction industry. Navigation and positioning is a very important task for construction robots, and the requirements for accuracy of positioning are very high. Traditional indoor robots mainly use radio frequency or vision methods for positioning. Compared with ordinary robots, the indoor plastering robot needs to be positioned closer to the wall for wall plastering, so the requirements for construction positioning accuracy are higher, and the traditional navigation positioning method has a large error, which will cause the robot to move. Without the exact position, the wall cannot be plastered or the error of plastering the wall is large. A positioning method is proposed, which is assisted by line lasers and uses image processing-based positioning to perform more accurate positioning on the traditional positioning work. In actual work, filter, edge detection, Hough transform and other operations are performed on the images captured by the camera. Each time the position of the laser line is found, it is compared with the standard value, and the position of the robot is moved or rotated to complete the positioning work. The experimental results show that the actual positioning error is reduced to less than 0.5 mm by this accurate positioning method.

Keywords: Indoor plastering robot, navigation, precise positioning, line laser, image processing.

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Authors: Nidhal Jamia, Sami El-Borgi

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In this paper, the problem of a mixed-Mode crack embedded in an infinite medium made of a functionally graded piezoelectric material (FGPM) with crack surfaces subjected to electro-mechanical loadings is investigated. Eringen’s non-local theory of elasticity is adopted to formulate the governing electro-elastic equations. The properties of the piezoelectric material are assumed to vary exponentially along a perpendicular plane to the crack. Using Fourier transform, three integral equations are obtained in which the unknown variables are the jumps of mechanical displacements and electric potentials across the crack surfaces. To solve the integral equations, the unknowns are directly expanded as a series of Jacobi polynomials, and the resulting equations solved using the Schmidt method. In contrast to the classical solutions based on the local theory, it is found that no mechanical stress and electric displacement singularities are present at the crack tips when nonlocal theory is employed to investigate the problem. A direct benefit is the ability to use the calculated maximum stress as a fracture criterion. The primary objective of this study is to investigate the effects of crack length, material gradient parameter describing FGPMs, and lattice parameter on the mechanical stress and electric displacement field near crack tips.

Keywords: Functionally graded piezoelectric material, mixed-mode crack, non-local theory, Schmidt method.

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Authors: Homa Torabizadeh, Mohaddeseh Mikani

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Inulinase from Aspergillus niger was covalently immobilized on magnetic nanoparticles (MNPs/Fe₃O₄) covered with soy protein isolate (SPI/Fe₃O₄) functionalized by bovine serum albumin (BSA) nanoparticles. MNPs are promising enzyme carriers because they separate easily under external magnetic fields and have enhanced immobilized enzyme reusability. As MNPs aggregate simply, surface coating strategy was employed. SPI functionalized by BSA was a suitable candidate for nanomagnetite coating due to its superior biocompatibility and hydrophilicity. Fe₃O₄@SPI-BSA nanoparticles were synthesized as a novel carrier with narrow particle size distribution. Step by step fabrication monitoring of Fe₃O₄@SPI-BSA nanoparticles was performed using field emission scanning electron microscopy and dynamic light scattering. The results illustrated that nanomagnetite with the spherical morphology was well monodispersed with the diameter of about 35 nm. The average size of the SPI-BSA nanoparticles was 80 to 90 nm, and their zeta potential was around −34 mV. Finally, the mean diameter of fabricated Fe₃O₄@SPI-BSA NPs was less than 120 nm. Inulinase enzyme from Aspergillus niger was covalently immobilized through gluteraldehyde on Fe₃O₄@SPI-BSA nanoparticles successfully. Fourier transform infrared spectra and field emission scanning electron microscopy images provided sufficient proof for the enzyme immobilization on the nanoparticles with 80% enzyme loading.

Keywords: High fructose syrup, inulinase immobilization, functionalized magnetic nanoparticles, soy protein isolate.

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Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

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In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other.

As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO.

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Authors: Vahidreza Mahmoudabadi, Omid Bahar, Mohammad Kazem Jafari

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In many applied engineering problems, structural analysis is usually conducted by assuming a rigid bed, while imposing the effect of structure bed flexibility can affect significantly on the structure response. This article focuses on investigation and evaluation of the effects arising from considering a soil-structure system in evaluation of dynamic characteristics of a steel structure with respect to elastic and inelastic behaviors. The recorded structure acceleration during Taiwan’s strong Chi-Chi earthquake on different floors of the structure was our evaluation criteria. The respective structure is an eight-story steel bending frame structure designed using a displacement-based direct method assuring weak beam - strong column function. The results indicated that different identification methods i.e. reverse Fourier transform or transfer functions, is capable to determine some of the dynamic parameters of the structure precisely, rather than evaluating all of them at once (mode frequencies, mode shapes, structure damping, structure rigidity, etc.). Response evaluation based on the input and output data elucidated that the structure first mode is not significantly affected, even considering the soil-structure interaction effect, but the upper modes have been changed. Also, it was found that the response transfer function of the different stories, in which plastic hinges have occurred in the structure components, provides similar results.

Keywords: System identification, dynamic characteristics, soil-structure system, bending steel frame structure, displacement-based design.

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Authors: Roshafima R. Ali, W. A. Wan Abdul Rahman, Rafiziana M. Kasmani, N. Ibrahim

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This current research focused on development of degradable starch based packaging film with enhanced mechanical properties. A series of low density polyethylene (LDPE)/tapioca starch compounds with various tapioca starch contents were prepared by twin screw extrusion with the addition of maleic anhydride grafted polyethylene as compatibilizer. Palm cooking oil was used as processing aid to ease the blown film process, thus, degradable film can be processed via conventional blown film machine. Studies on their characteristics, mechanical properties and biodegradation were carried out by Fourier Transform Infrared (FTIR) spectroscopy and optical properties, tensile test and exposure to fungi environment respectively. The presence of high starch contents had an adverse effect on the tensile properties of LDPE/tapioca starch blends. However, the addition of compatibilizer to the blends improved the interfacial adhesion between the two materials, hence, improved the tensile properties of the films. High content of starch amount also was found to increase the rate of biodegradability of LDPE/tapioca starch films. It can be proved by exposure of the film to fungi environment. A growth of microbes colony can be seen on the surface of LDPE/tapioca starch film indicates that the granular starch present on the surface of the polymer film is attacked by microorganisms, until most of it is assimilated as a carbon source.

Keywords: Degradable polymer, starch based biofilms, blown film extrusion, green food packaging.

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

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In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: Brain-computer interface, speech recognition, electroencephalography EEG, Wernicke area, artificial neural network.

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Authors: Jason Chien-Hsun Tseng

Abstract:

This paper evaluates performances of an adaptive noise cancelling (ANC) based target detection algorithm on a set of real test data supported by the Defense Evaluation Research Agency (DERA UK) for multi-target wideband active sonar echolocation system. The hybrid algorithm proposed is a combination of an adaptive ANC neuro-fuzzy scheme in the first instance and followed by an iterative optimum target motion estimation (TME) scheme. The neuro-fuzzy scheme is based on the adaptive noise cancelling concept with the core processor of ANFIS (adaptive neuro-fuzzy inference system) to provide an effective fine tuned signal. The resultant output is then sent as an input to the optimum TME scheme composed of twogauge trimmed-mean (TM) levelization, discrete wavelet denoising (WDeN), and optimal continuous wavelet transform (CWT) for further denosing and targets identification. Its aim is to recover the contact signals in an effective and efficient manner and then determine the Doppler motion (radial range, velocity and acceleration) at very low signal-to-noise ratio (SNR). Quantitative results have shown that the hybrid algorithm have excellent performance in predicting targets- Doppler motion within various target strength with the maximum false detection of 1.5%.

Keywords: Wideband Active Sonar Echolocation, ANC Neuro-Fuzzy, Wavelet Denoise, CWT, Hybrid Algorithm.

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Authors: Bimali Sanjeevani Weerakoon, Toshiaki Osuga, Takehisa Konishi

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Magnetic Resonance Imaging Contrast Agents (MRI-CM) are significant in the clinical and biological imaging as they have the ability to alter the normal tissue contrast, thereby affecting the signal intensity to enhance the visibility and detectability of images. Superparamagnetic Iron Oxide (SPIO) nanoparticles, coated with dextran or carboxydextran are currently available for clinical MR imaging of the liver. Most SPIO contrast agents are T2 shortening agents and Resovist (Ferucarbotran) is one of a clinically tested, organ-specific, SPIO agent which has a low molecular carboxydextran coating. The enhancement effect of Resovist depends on its relaxivity which in turn depends on factors like magnetic field strength, concentrations, nanoparticle properties, pH and temperature. Therefore, this study was conducted to investigate the impact of field strength and different contrast concentrations on enhancement effects of Resovist. The study explored the MRI signal intensity of Resovist in the physiological range of plasma from T2-weighted spin echo sequence at three magnetic field strengths: 0.47 T (r1=15, r2=101), 1.5 T (r1=7.4, r2=95), and 3 T (r1=3.3, r2=160) and the range of contrast concentrations by a mathematical simulation. Relaxivities of r1 and r2 (L mmol-1 Sec-1) were obtained from a previous study and the selected concentrations were 0.05, 0.06, 0.07, 0.08, 0.09, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 2.0, and 3.0 mmol/L. T2-weighted images were simulated using TR/TE ratio as 2000 ms /100 ms. According to the reference literature, with increasing magnetic field strengths, the r1 relaxivity tends to decrease while the r2 did not show any systematic relationship with the selected field strengths. In parallel, this study results revealed that the signal intensity of Resovist at lower concentrations tends to increase than the higher concentrations. The highest reported signal intensity was observed in the low field strength of 0.47 T. The maximum signal intensities for 0.47 T, 1.5 T and 3 T were found at the concentration levels of 0.05, 0.06 and 0.05 mmol/L, respectively. Furthermore, it was revealed that, the concentrations higher than the above, the signal intensity was decreased exponentially. An inverse relationship can be found between the field strength and T2 relaxation time, whereas, the field strength was increased, T2 relaxation time was decreased accordingly. However, resulted T2 relaxation time was not significantly different between 0.47 T and 1.5 T in this study. Moreover, a linear correlation of transverse relaxation rates (1/T2, s–1) with the concentrations of Resovist can be observed. According to these results, it can conclude that the concentration of SPIO nanoparticle contrast agents and the field strengths of MRI are two important parameters which can affect the signal intensity of T2-weighted SE sequence. Therefore, when MR imaging those two parameters should be considered prudently.

Keywords: Concentration, Resovist, Field strength, Relaxivity, Signal intensity.

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Authors: Mbainaibeye Jérôme, Noureddine Ellouze

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We study in this paper the effect of the scene changing on image sequences coding system using Embedded Zerotree Wavelet (EZW). The scene changing considered here is the full motion which may occurs. A special image sequence is generated where the scene changing occurs randomly. Two scenarios are considered: In the first scenario, the system must provide the reconstruction quality as best as possible by the management of the bit rate (BR) while the scene changing occurs. In the second scenario, the system must keep the bit rate as constant as possible by the management of the reconstruction quality. The first scenario may be motivated by the availability of a large band pass transmission channel where an increase of the bit rate may be possible to keep the reconstruction quality up to a given threshold. The second scenario may be concerned by the narrow band pass transmission channel where an increase of the bit rate is not possible. In this last case, applications for which the reconstruction quality is not a constraint may be considered. The simulations are performed with five scales wavelet decomposition using the 9/7-tap filter bank biorthogonal wavelet. The entropy coding is performed using a specific defined binary code book and EZW algorithm. Experimental results are presented and compared to LEAD H263 EVAL. It is shown that if the reconstruction quality is the constraint, the system increases the bit rate to obtain the required quality. In the case where the bit rate must be constant, the system is unable to provide the required quality if the scene change occurs; however, the system is able to improve the quality while the scene changing disappears.

Keywords: Image Sequence Compression, Wavelet Transform, Scene Changing, Zero Tree, Bit Rate, Quality.

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Authors: Eraricar Salleh, Ida Idayu Muhamad, Nozieanna Khairuddin

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Antimicrobial (AM) starch-based films were developed by incorporating chitosan and lauric acid as antimicrobial agent into starch-based film. Chitosan has wide range of applications as a biomaterial, but barriers still exist to its broader use due to its physical and chemical limitations. In this work, a series of starch/chitosan (SC) blend films containing 8% of lauric acid was prepared by casting method. The structure of the film was characterized by Fourier transform infrared spectroscopy (FTIR), Xray diffraction (XRD), and scanning electron microscopy (SEM). The results indicated that there were strong interactions were present between the hydroxyl groups of starch and the amino groups of chitosan resulting in a good miscibility between starch and chitosan in the blend films. Physical properties and optical properties of the AM starch-based film were evaluated. The AM starch-based films incorporated with chitosan and lauric acid showed an improvement in water vapour transmission rate (WVTR) and addition of starch content provided more transparent films while the yellowness of the film attributed to the higher chitosan content. The improvement in water barrier properties was mainly attributed to the hydrophobicity of lauric acid and optimum chitosan or starch content. AM starch based film also showed excellent oxygen barrier. Obtaining films with good oxygen permeability would be an indication of the potential use of these antimicrobial packaging as a natural packaging and an alternative packaging to the synthetic polymer to protect food from oxidation reactions

Keywords: Antimicrobial starch-based films, chitosan, lauric acid, starch.

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Authors: M. A. Kassim, R. Potumarthi, A. Tanksale, S. C. Srivatsa, S. Bhattacharya

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Enzymatic saccharification of biomass for reducing sugar production is one of the crucial processes in biofuel production through biochemical conversion. In this study, enzymatic saccharification of dilute potassium hydroxide (KOH) pre-treated Tetraselmis suecica biomass was carried out by using cellulase enzyme obtained from Trichoderma longibrachiatum. Initially, the pre-treatment conditions were optimised by changing alkali reagent concentration, retention time for reaction, and temperature. The T. suecica biomass after pre-treatment was also characterized using Fourier Transform Infrared Spectra and Scanning Electron Microscope. These analyses revealed that the functional group such as acetyl and hydroxyl groups, structure and surface of T. suecica biomass were changed through pre-treatment, which is favourable for enzymatic saccharification process. Comparison of enzymatic saccharification of untreated and pre-treated microalgal biomass indicated that higher level of reducing sugar can be obtained from pre-treated T. suecica. Enzymatic saccharification of pre-treated T. suecica biomass was optimised by changing temperature, pH, and enzyme concentration to solid ratio ([E]/[S]). Highest conversion of carbohydrate into reducing sugar of 95% amounted to reducing sugar yield of 20 (wt%) from pre-treated T. suecica was obtained from saccharification, at temperature: 40°C, pH: 4.5 and [E]/[S] of 0.1 after 72 h of incubation. Hydrolysate obtained from enzymatic saccharification of pretreated T. suecica biomass was further fermented into biobutanol using Clostridium saccharoperbutyliticum as biocatalyst. The results from this study demonstrate a positive prospect of application of dilute alkaline pre-treatment to enhance enzymatic saccharification and biobutanol production from microalgal biomass.

Keywords: Microalgal biomass, enzymatic saccharification, biobutanol, fermentation.

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Authors: B. Vadiraj, S. N. Omkar, B. Kapil Bharadwaj, Yash Vardhan Gupta

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During manned exploration of space, missions will require astronaut crewmembers to perform Extra Vehicular Activities (EVAs) for a variety of tasks. These EVAs take place after long periods of operations in space, and in and around unique vehicles, space structures and systems. Considering the remoteness and time spans in which these vehicles will operate, EVA system operations should utilize common worksites, tools and procedures as much as possible to increase the efficiency of training and proficiency in operations. All of the preparations need to be carried out based on studies of astronaut motions. Until now, development and training activities associated with the planned EVAs in Russian and U.S. space programs have relied almost exclusively on physical simulators. These experimental tests are expensive and time consuming. During the past few years a strong increase has been observed in the use of computer simulations due to the fast developments in computer hardware and simulation software. Based on this idea, an effort to develop a computational simulation system to model human dynamic motion for EVA is initiated. This study focuses on the simulation of an astronaut moving the orbital replaceable units into the worksites or removing them from the worksites. Our physics-based methodology helps fill the gap in quantitative analysis of astronaut EVA by providing a multisegment human arm model. Simulation work described in the study improves on the realism of previous efforts, incorporating joint stops to account for the physiological limits of range of motion. To demonstrate the utility of this approach human arm model is simulated virtually using ADAMS/LifeMOD^® software. Kinematic mechanism for the astronaut’s task is studied from joint angles and torques. Simulation results obtained is validated with numerical simulation based on the principles of Newton-Euler method. Torques determined using mathematical model are compared among the subjects to know the grace and consistency of the task performed. We conclude that due to uncertain nature of exploration-class EVA, a virtual model developed using multibody dynamics approach offers significant advantages over traditional human modeling approaches.

Keywords: Extra vehicular activity, biomechanics, inverse kinematics, human body modeling.

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Authors: H. K. G. K. D. K. Hapuhinna, R. D. Gunaratne, H. M. J. C. Pitawala

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Hydroxyapatite is a bioceramic which can be used for applications in orthopedics and dentistry due to its structural similarity with the mineral phase of mammalian bones and teeth. In this study, it was synthesized, chemically changing natural Eppawala chloroapatite mineral as a value-added product. Sol-gel approach and solid state sintering were used to synthesize products using diluted nitric acid, ethanol and calcium hydroxide under different conditions. Synthesized Eppawala hydroxyapatite powder was characterized using X-ray Fluorescence (XRF), X-ray Powder Diffraction (XRD), Fourier-transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), Thermogravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC) in order to find out its composition, crystallinity, presence of functional groups, bonding type, surface morphology, microstructural features, and thermal dependence and stability, respectively. The XRD results reflected the formation of a hexagonal crystal structure of hydroxyapatite. Elementary composition and microstructural features of products were discussed based on the XRF and SEM results of the synthesized hydroxyapatite powder. TGA and DSC results of synthesized products showed high thermal stability and good material stability in nature. Also, FTIR spectroscopy results confirmed the formation of hydroxyapatite from apatite via the presence of hydroxyl groups. Those results coincided with the FTIR results of mammalian bones including human bones. The study concludes that there is a possibility of producing hydroxyapatite using commercially available Eppawala chloroapatite in Sri Lanka.

Keywords: Dentistry, eppawala chloroapatite, hydroxyapatite, orthopedics.

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Authors: A. Bajit, M. Nahid, A. Tamtaoui, E. H. Bouyakhf

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In this paper, we propose a Perceptually Optimized Embedded ZeroTree Image Coder (POEZIC) that introduces a perceptual weighting to wavelet transform coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to the coding quality obtained using the SPIHT algorithm only. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEZIC quality assessment. Our POEZIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) luminance masking and Contrast masking, 2) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting, 3) the Wavelet Error Sensitivity WES used to reduce the perceptual quantization errors. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.

Keywords: DWT, linear-phase 9/7 filter, 9/7 Wavelets Error Sensitivity WES, CSF implementation approaches, JND Just Noticeable Difference, Luminance masking, Contrast masking, standard SPIHT, Objective Quality Measure, Probability Score PS.

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Authors: Hazem M. El-Bakry

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In this paper, an automatic determination algorithm for nuclear magnetic resonance (NMR) spectra of the metabolites in the living body by magnetic resonance spectroscopy (MRS) without human intervention or complicated calculations is presented. In such method, the problem of NMR spectrum determination is transformed into the determination of the parameters of a mathematical model of the NMR signal. To calculate these parameters efficiently, a new model called modified Hopfield neural network is designed. The main achievement of this paper over the work in literature [30] is that the speed of the modified Hopfield neural network is accelerated. This is done by applying cross correlation in the frequency domain between the input values and the input weights. The modified Hopfield neural network can accomplish complex dignals perfectly with out any additinal computation steps. This is a valuable advantage as NMR signals are complex-valued. In addition, a technique called “modified sequential extension of section (MSES)" that takes into account the damping rate of the NMR signal is developed to be faster than that presented in [30]. Simulation results show that the calculation precision of the spectrum improves when MSES is used along with the neural network. Furthermore, MSES is found to reduce the local minimum problem in Hopfield neural networks. Moreover, the performance of the proposed method is evaluated and there is no effect on the performance of calculations when using the modified Hopfield neural networks.

Keywords: Hopfield Neural Networks, Cross Correlation, Nuclear Magnetic Resonance, Magnetic Resonance Spectroscopy, Fast Fourier Transform.

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Authors: Feng Ge, Tiecheng Liu, Song Wang, Joachim Stahl

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This paper presents a novel template-based method to detect objects of interest from real images by shape matching. To locate a target object that has a similar shape to a given template boundary, the proposed method integrates three components: contour grouping, partial shape matching, and boundary verification. In the first component, low-level image features, including edges and corners, are grouped into a set of perceptually salient closed contours using an extended ratio-contour algorithm. In the second component, we develop a partial shape matching algorithm to identify the fractions of detected contours that partly match given template boundaries. Specifically, we represent template boundaries and detected contours using landmarks, and apply a greedy algorithm to search the matched landmark subsequences. For each matched fraction between a template and a detected contour, we estimate an affine transform that transforms the whole template into a hypothetic boundary. In the third component, we provide an efficient algorithm based on oriented edge lists to determine the target boundary from the hypothetic boundaries by checking each of them against image edges. We evaluate the proposed method on recognizing and localizing 12 template leaves in a data set of real images with clutter back-grounds, illumination variations, occlusions, and image noises. The experiments demonstrate the high performance of our proposed method1.

Keywords: Object detection, shape matching, contour grouping.

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Authors: Siham Jemal Kedir

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Information communication technology is dramatically transforming the health sector, especially in developing countries with few resources and burgeoning access to an internet connection. As a result, processes such as record keeping, administration, and human resources have been vastly simplified, allowing hospitals to focus on delivering urgent medical care. This paper will explore the impact of IT through a study of the electronic medical record system in the Mekelle City Health Center in Tigray Region, Ethiopia. This paper has four specific objectives: 1. developing artifacts in the Electronic Medical Record system, 2. preparing a diagram for step-by-step development of Electronic Medical Records, 3. creating a draft website with the proposed Electronic Medical Record system, and 4. Testing and evaluating the performance and user acceptance of the system. The research will be done in a qualitative manner employing interviews and in-person observation. The research has found the following major results: firstly, the medical record system has been difficult to implement. Second, the Mekelle Health Center is using a manual recording system which is time-consuming and inefficient. The old recording system in the Center leads to the dissatisfaction of patients as well as the service provider staff. As a result, to transform the manual recording system into a digital system, an electronic medical recording system has been developed. The developed system has been tested for implementation and has been successful. Consequently, the administrator of the health center is ready to implement and use the developed software to introduce a medical recording system in Mekelle Health Center.

Keywords: Electronic Health Record Implementation, EMR System Development, Medical Record.

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Authors: Mohamad Reza. Mohaghegh, Majid. Malek Jafarian

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This research proposes an algorithm for the simulation of time-periodic unsteady problems via the solution unsteady Euler and Navier-Stokes equations. This algorithm which is called Time Spectral method uses a Fourier representation in time and hence solve for the periodic state directly without resolving transients (which consume most of the resources in a time-accurate scheme). Mathematical tools used here are discrete Fourier transformations. It has shown tremendous potential for reducing the computational cost compared to conventional time-accurate methods, by enforcing periodicity and using Fourier representation in time, leading to spectral accuracy. The accuracy and efficiency of this technique is verified by Euler and Navier-Stokes calculations for pitching airfoils. Because of flow turbulence nature, Baldwin-Lomax turbulence model has been used at viscous flow analysis. The results presented by the Time Spectral method are compared with experimental data. It has shown tremendous potential for reducing the computational cost compared to the conventional time-accurate methods, by enforcing periodicity and using Fourier representation in time, leading to spectral accuracy, because results verify the small number of time intervals per pitching cycle required to capture the flow physics.

Keywords: Time Spectral Method, Time-periodic unsteadyflow, Discrete Fourier transform, Pitching airfoil, Turbulence flow

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Authors: B. Elshafei, X. Mao

Abstract:

The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: Data fusion, Gaussian process regression, signal denoise, temporal extrapolation.

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