Search results for: boundary layer noise denoising

Authors: Chia Jui Hsieh, Jyh Cheng Chen, Chih Wei Kuo, Ruei Teng Wang, Woei Chyn Chu

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Compressed sensing (CS) based computed tomographic (CT) reconstruction algorithm utilizes total variation (TV) to transform CT image into sparse domain and minimizes L1-norm of sparse image for reconstruction. Different from the traditional CS based reconstruction which only calculates x-coordinate and y-coordinate TV to transform CT images into sparse domain, we propose a multi-directional TV to transform tomographic image into sparse domain for low-dose reconstruction. Our method considers all possible directions of TV calculations around a pixel, so the sparse transform for CS based reconstruction is more accurate. In 2D CT reconstruction, we use eight-directional TV to transform CT image into sparse domain. Furthermore, we also use 26-directional TV for 3D reconstruction. This multi-directional sparse transform method makes CS based reconstruction algorithm more powerful to reduce noise and increase image quality. To validate and evaluate the performance of this multi-directional sparse transform method, we use both Shepp-Logan phantom and a head phantom as the targets for reconstruction with the corresponding simulated sparse projection data (angular sampling interval is 5 deg and 6 deg, respectively). From the results, the multi-directional TV method can reconstruct images with relatively less artifacts compared with traditional CS based reconstruction algorithm which only calculates x-coordinate and y-coordinate TV. We also choose RMSE, PSNR, UQI to be the parameters for quantitative analysis. From the results of quantitative analysis, no matter which parameter is calculated, the multi-directional TV method, which we proposed, is better.

Keywords: compressed sensing (CS), low-dose CT reconstruction, total variation (TV), multi-directional gradient operator

Procedia PDF Downloads 256

Authors: S. S. Kharintsev, E. A. Chernykh, S. K. Saikin, A. I. Fishman, S. G. Kazarian

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Recent advances in improving information storage performance are inseparably linked with circumvention of fundamental constraints such as the supermagnetic limit in heat assisted magnetic recording, charge loss tolerance in solid-state memory and the Abbe’s diffraction limit in optical storage. A substantial breakthrough in the development of nonvolatile storage devices with dimensional scaling has been achieved due to phase-change chalcogenide memory, which nowadays, meets the market needs to the greatest advantage. A further progress is aimed at the development of versatile nonvolatile high-speed memory combining potentials of random access memory and archive storage. The well-established properties of light at the nanoscale empower us to use them for recording optical information with ultrahigh density scaled down to a single molecule, which is the size of a pit. Indeed, diffraction-limited optics is able to record as much information as ~1 Gb/in2. Nonlinear optical effects, for example, two-photon fluorescence recording, allows one to decrease the extent of the pit even more, which results in the recording density up to ~100 Gb/in2. Going beyond the diffraction limit, due to the sub-wavelength confinement of light, pushes the pit size down to a single chromophore, which is, on average, of ~1 nm in length. Thus, the memory capacity can be increased up to the theoretical limit of 1 Pb/in2. Moreover, the field confinement provides faster recording and readout operations due to the enhanced light-matter interaction. This, in turn, leads to the miniaturization of optical devices and the decrease of energy supply down to ~1 μW/cm². Intrinsic features of light such as multimode, mixed polarization and angular momentum in addition to the underlying optical and holographic tools for writing/reading, enriches the storage and encryption of optical information. In particular, the finite extent of the near-field penetration, falling into a range of 50-100 nm, gives the possibility to perform 3D volume (layer-to-layer) recording/readout of optical information. In this study, we demonstrate a comprehensive evidence of isotropic-to-homeotropic phase transition of the azobenzene-functionalized polymer thin film exposed to light and dc electric field using near-field optical microscopy and scanning capacitance microscopy. We unravel a near-field Raman dichroism of a sub-10 nm thick epoxy-based side-chain azo-polymer films with polarization-controlled tip-enhanced Raman scattering. In our study, orientation of azo-chromophores is controlled with a bias voltage gold tip rather than light polarization. Isotropic in-plane and homeotropic out-of-plane arrangement of azo-chromophores in glassy environment can be distinguished with transverse and longitudinal optical near-fields. We demonstrate that both phases are unambiguously visualized by 2D mapping their local dielectric properties with scanning capacity microscopy. The stability of the polar homeotropic phase is strongly sensitive to the thickness of the thin film. We make an analysis of α-transition of the azo-polymer by detecting a temperature-dependent phase jump of an AFM cantilever when passing through the glass temperature. Overall, we anticipate further improvements in optical storage performance, which approaches to a single molecule level.

Keywords: optical memory, azo-dye, near-field, tip-enhanced Raman scattering

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Authors: A.G. S. Aldajani, N. Smida, M. G. Althobaiti, B. Zaidi

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In order to exploit the good electrical properties of anthracene and the excellent properties of fluorescein, new hybrid material has been synthesized (An-Fl). Current-voltage measurements were done on a new single-layer ITO/An-FL/Al device of typically 100 nm thickness. Atypical diode behavior is observed with a turn-on voltage of 4.4 V, a dynamic resistance of 74.07 KΩ and a rectification ratio of 2.02 due to unbalanced transport. Results show also that the current-voltage characteristics present three different regimes of the power-law (J~Vᵐ) for which the conduction mechanism is well described with space-charge-limited current conduction mechanism (SCLC) with a charge carrier mobility of 2.38.10⁻⁵cm2V⁻¹S⁻¹. Moreover, the electrical transport properties of this device have been carried out using a dependent frequency study in the range (50 Hz–1.4 MHz) for different applied biases (from 0 to 6 V). At lower frequency, the σdc values increase with bias voltage rising, supporting that the mobile ion can hop successfully to its nearest vacant site. From σac and impedance measurements, the equivalent electrical circuit is evidenced, where the conductivity process is coherent with an exponential trap distribution caused by structural defects and/or chemical impurities.

Keywords: semiconducting polymer, conductivity, SCLC, impedance spectroscopy

Procedia PDF Downloads 179

Authors: Khor Khai Ling, Vashnarekha A/P Kumarasuriar, Tan Kok Wei, Ooi Pei Boon

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The food pyramid had been stressed for years and used to promote a healthy diet. Recently, the Ministry of Health in Malaysia has changed the food pyramid structure. They moved fruits and vegetables to the bottom layer and encouraged citizens to consume more fruits and vegetables. Past research has shown that the amount of vegetables and fruits consumption has associated with cognitive health. However, Malaysians have yet to achieve the amount of fruit and vegetable intake as per recommendation. Thus, this study aims to investigate Malaysian’s habitual diet and cognitive functioning via a cross-sectional study. One hundred and ninety-three participants will be recruited via convenient sampling. A Food Frequency Questionnaire (FFQ) measures the habitual diet, and an online cognitive test measures attention, executive functioning, and memory objectively. The collected one hundred samples to the date of abstract submission, and the data collection is still in progress. This study will provide an insight to Malaysian about the diet pattern and its relationship with cognitive performance.

Keywords: attention, cognitive, executive functioning, habitual diet, memory

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Authors: Menouni Aziza, Chbihi Kaoutar, Duca Radu Corneliu, Gilissen Liesbeth, Bounou Salim, Godderis Lode, El Jaafari Samir

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In Africa, environmental and occupational health risks are mostly underreported. The aim of this research is to develop and implement a sentinel surveillance system comprising training and guidance of occupational physicians (OC) who will report new work-related diseases in African countries. A group of 30 OC are recruited and trained in each of the partner countries (Morocco, Benin and Ethiopia). Each committed OC is asked to recruit 50 workers during a consultation in a time-frame of 6 months (1500 workers per country). Workers are asked to fill out an online questionnaire about their health status and work conditions, including exposure to 20 chemicals. Urine and blood samples are then collected for human biomonitoring of common exposures. Some preliminary results showed that 92% of the employees surveyed are exposed to physical constraints, 44% to chemical agents, and 24% to biological agents. The most common physical constraints are manual handling of loads, noise pollution and thermal pollution. The most frequent chemical risks are exposure to pesticides and fuels. This project will allow a better understanding of effective sentinel systems as a promising method to gather high quality data, which can support policy-making in terms of preventing emerging work-related diseases.

Keywords: sentinel system, occupational diseases, human biomonitoring, Africa

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Authors: Subir Gupta, Subhas Ganguly

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In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

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Authors: Abhishek Saha, Serene Tay, Gerard Pijcke

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The availability of high-resolution topography and rainfall information in urban areas has made it necessary to revise modeling approaches used for simulating flood risk assessments. Lidar derived elevation models that have 1m or lower resolutions are becoming widely accessible. The classical approaches of 1D-2D flow models where channel flow is simulated and coupled with a coarse resolution 2D overland flow models may not fully utilize the information provided by high-resolution data. In this context, a study was undertaken to compare three different modeling approaches to simulate flooding in an urban area. The first model used is the base model used is Sobek, which uses 1D model formulation together with hydrologic boundary conditions and couples with an overland flow model in 2D. The second model uses a full 2D model for the entire area with shallow water equations at the resolution of the digital elevation model (DEM). These models are compared against another shallow water equation solver in 2D, which uses a subgrid method for grid refinement. These models are simulated for different horizontal resolutions of DEM varying between 1m to 5m. The results show a significant difference in inundation extents and water levels for different DEMs. They are also sensitive to the different numerical models with the same physical parameters, such as friction. The study shows the importance of having reliable field observations of inundation extents and levels before a choice of model and data can be made for spatial flood risk assessments.

Keywords: flooding, DEM, shallow water equations, subgrid

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Authors: Atif Zafar, Fan Haijun

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A sequence of different Reservoir Engineering methods and tools in reservoir characterization and field development are presented in this paper. The real data of Jin Gas Field of L-Basin of Pakistan is used. The basic concept behind this work is to enlighten the importance of well test analysis in a broader way (i.e. reservoir characterization and field development) unlike to just determine the permeability and skin parameters. Normally in the case of reservoir characterization we rely on well test analysis to some extent but for field development plan, the well test analysis has become a forgotten tool specifically for locations of new development wells. This paper describes the successful implementation of well test analysis in Jin Gas Field where the main uncertainties are identified during initial stage of field development when location of new development well was marked only on the basis of G&G (Geologic and Geophysical) data. The seismic interpretation could not encounter one of the boundary (fault, sub-seismic fault, heterogeneity) near the main and only producing well of Jin Gas Field whereas the results of the model from the well test analysis played a very crucial rule in order to propose the location of second well of the newly discovered field. The results from different methods of well test analysis of Jin Gas Field are also integrated with and supported by other tools of Reservoir Engineering i.e. Material Balance Method and Volumetric Method. In this way, a comprehensive way out and algorithm is obtained in order to integrate the well test analyses with Geological and Geophysical analyses for reservoir characterization and field development. On the strong basis of this working and algorithm, it was successfully evaluated that the proposed location of new development well was not justified and it must be somewhere else except South direction.

Keywords: field development plan, reservoir characterization, reservoir engineering, well test analysis

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Authors: Irene Carmagnola, Valeria Chiono, Sandra Pacharra, Jochen Salber, Sean McMahon, Chris Lovell, Pooja Basnett, Barbara Lukasiewicz, Ipsita Roy, Xiang Zhang, Gianluca Ciardelli

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Thrombosis and restenosis after stenting procedure can be prevented by promoting fast stent wall endothelialisation. It is well known that surface functionalisation with antifouling molecules combining with extracellular matrix proteins is a promising strategy to design biomimetic surfaces able to promote fast endothelialization. In particular, REDV has gained much attention for the ability to enhance rapid endothelialization due to its specific affinity with endothelial cells (ECs). In this work, a two-step plasma treatment was performed to polymerize a thin layer of acrylic acid, used to subsequently graft PEGylated-REDV and polyethylene glycol (PEG) at different molar ratio with the aim to selectively promote endothelial cell adhesion avoiding platelet activation. PEGylate-REDV was provided by Biomatik and it is formed by 6 PEG monomer repetitions (Chempep Inc.), with an NH2 terminal group. PEG polymers were purchased from Chempep Inc. with two different chain lengths: m-PEG6-NH2 (295.4 Da) with 6 monomer repetitions and m-PEG12-NH2 (559.7 Da) with 12 monomer repetitions. Plasma activation was obtained by operating at 50W power, 5 min of treatment and at an Ar flow rate of 20 sccm. Pure acrylic acid (99%, AAc) vapors were diluted in Ar (flow = 20 sccm) and polymerized by a pulsed plasma discharge applying a discharge RF power of 200 W, a duty cycle of 10% (on time = 10 ms, off time = 90 ms) for 10 min. After plasma treatment, samples were dipped into an 1-(3-dimethylaminopropyl)-3- ethylcarbodiimide (EDC)/N-hydroxysuccinimide (NHS) solution (ratio 4:1, pH 5.5) for 1 h at 4°C and subsequently dipped in PEGylate-REDV and PEGylate-REDV:PEG solutions at different molar ratio (100 μg/mL in PBS) for 20 h at room temperature. Surface modification was characterized through physico-chemical analyses and in vitro cell tests. PEGylated-REDV peptide and PEG were successfully bound to the carboxylic groups that are formed on the polymer surface after plasma reaction. FTIR-ATR spectroscopy, X -ray Photoelectron Spectroscopy (XPS) and contact angle measurement gave a clear indication of the presence of the grafted molecules. The use of PEG as a spacer allowed for an increase in wettability of the surface, and the effect was more evident by increasing the amount of PEG. Endothelial cells adhered and spread well on the surfaces functionalized with the REDV sequence. In conclusion, a selective coating able to promote a new endothelial cell layer on polymeric stent surface was developed. In particular, a thin AAc film was polymerised on the polymeric surface in order to expose –COOH groups, and PEGylate-REDV and PEG were successful grafted on the polymeric substrates. The REDV peptide demonstrated to encourage cell adhesion with a consequent, expected improvement of the hemocompatibility of these polymeric surfaces in vivo. Acknowledgements— This work was funded by the European Commission 7th Framework Programme under grant agreement number 604251- ReBioStent (Reinforced Bioresorbable Biomaterials for Therapeutic Drug Eluting Stents). The authors thank all the ReBioStent partners for their support in this work.

Keywords: endothelialisation, plasma treatment, stent, surface functionalisation

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Authors: Zoran Šverko, Saša Vlahinić, Nino Stojković, Ivan Markovinović

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In this article, the classification of target letters is performed using data from the EEG P300 Speller paradigm. Neural networks trained with the results of dynamic connectivity analysis between different brain regions are used for classification. Dynamic connectivity analysis is based on the adaptive window size and the imaginary part of the complex Pearson correlation coefficient. Brain dynamics are analysed using the relative intersection of confidence intervals for the imaginary component of the complex Pearson correlation coefficient method (RICI-imCPCC). The RICI-imCPCC method overcomes the shortcomings of currently used dynamical connectivity analysis methods, such as the low reliability and low temporal precision for short connectivity intervals encountered in constant sliding window analysis with wide window size and the high susceptibility to noise encountered in constant sliding window analysis with narrow window size. This method overcomes these shortcomings by dynamically adjusting the window size using the RICI rule. This method extracts information about brain connections for each time sample. Seventy percent of the extracted brain connectivity information is used for training and thirty percent for validation. Classification of the target word is also done and based on the same analysis method. As far as we know, through this research, we have shown for the first time that dynamic connectivity can be used as a parameter for classifying EEG signals.

Keywords: dynamic connectivity analysis, EEG, neural networks, Pearson correlation coefficients

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Authors: A. Khodabakhshi, A. Mortazavi

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Accurate determination of rock mass deformation modulus, as an important design parameter, is one of the most controversial issues in most engineering projects. A 3D numerical model of standard plate load test (PLT) using the FLAC3D code was carried to investigate the mechanism governing the test process. Five objectives were the focus of this study. The first goal was to employ 3D modeling in the interpretation of PLT conducted at the Bazoft dam site, Iran. The second objective was to investigate the effect of displacements measuring depth from the loading plates on the calculated moduli. The magnitude of rock mass deformation modulus calculated from PLT depends on anchor depth, and in practice, this may be a cause of error in the selection of realistic deformation modulus for the rock mass. The third goal of the study was to investigate the effect of testing plate diameter on the calculated modulus. Moreover, a comparison of the calculated modulus from ISRM formula, numerical modeling and calculated modulus from the actual PLT carried out at right abutment of the Bazoft dam site was another objective of the study. Finally, the effect of plastic strains on the calculated moduli in each of the loading-unloading cycles for three loading plates was investigated. The geometry, material properties, and boundary conditions on the constructed 3D model were selected based on the in-situ conditions of PLT at Bazoft dam site. A good agreement was achieved between numerical model results and the field tests results.

Keywords: deformation modulus, numerical model, plate loading test, rock mass

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Authors: Mahdi Fakoor, Seyed Mohammad Navid Ghoreishi

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Composite patching is a common way for reinforcing the cracked pipes and cylinders. The effects of composite patch reinforcement on fracture parameters of a cracked pipe depend on a variety of parameters such as number of layers, angle, thickness, and material of each layer. Therefore, stacking sequence optimization of composite patch becomes crucial for the applications of cracked pipes. In this study, in order to obtain the optimal stacking sequence for a composite patch that has minimum weight and maximum resistance in propagation of cracks, a coupled Multi-Objective Genetic Algorithm (MOGA) and Finite Element Method (FEM) process is proposed. This optimization process has done for longitudinal and transverse semi-elliptical cracks and optimal stacking sequences and Pareto’s front for each kind of cracks are presented. The proposed algorithm is validated against collected results from the existing literature.

Keywords: multi objective optimization, pareto front, composite patch, cracked pipe

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Authors: A. S. Bouchikhi, A. Megueni, S. Habibi

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One major problem when using bonded Fiber Reinforced Polymer is the presence of high inter facial stresses near the end of the composite laminate which might govern the failure of the strengthening schedule. It is known that the decrease of FRP plate thickness and the fitness of adhesive reduce the stress concentration at plate ends. Another way is to use a plate with a non uniform section or tapered ends and softer adhesive at the edges. In this paper, a comprehensive finite element (FE) study has been conducted to investigate the effect of mixed adhesive joints (MAJ) and tapering plate on the inter facial stress distribution in the adhesive layer, this paper presents the results of a study of application of two adhesives with different stiffnesses (bi-adhesive) along the joint strength length between the CFRP-strengthened steel beam for tapered and untapered plate on the distribution of inter facial stresses. A stiff adhesive was applied in the middle portion of the joint strength, while a low modulus adhesive was applied towards the edges prone to stress concentrations.

Keywords: FRP, mixed adhesive joints, stresses, tapered plate, retrofitted beams bonded

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Authors: Zhaofeng Li, Jun Kang Chow, Yu-Hsing Wang

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This paper attempts to bridge the soil properties and the mechanical response of soil in the discrete element method (DEM) simulation. The artificial neural network (ANN) was therefore adopted, aiming to reproduce the stress-strain-volumetric response when soil properties are given. 31 biaxial shearing tests with varying soil parameters (e.g., initial void ratio and interparticle friction coefficient) were generated using the DEM simulations. Based on these 45 sets of training data, a three-layer neural network was established which can output the entire stress-strain-volumetric curve during the shearing process from the input soil parameters. Beyond the training data, 2 additional sets of data were generated to examine the validity of the network, and the stress-strain-volumetric curves for both cases were well reproduced using this network. Overall, the ANN was found promising in predicting the soil behavior and reducing repetitive simulation work.

Keywords: artificial neural network, discrete element method, soil properties, stress-strain-volumetric response

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Authors: Yas Barzegaar, Atrin Barzegar

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The aim of this research is to develop an intelligent system to analyze the risk level of wheat flour product manufacturing system. The model consists of five Fuzzy Inference Systems in two different layers to analyse the risk of a wheat flour product manufacturing system. The first layer of the model consists of four Fuzzy Inference Systems with three criteria. The output of each one of the Physical, Chemical, Biological and Environmental Failures will be the input of the final manufacturing systems. The proposed model based on Mamdani Fuzzy Inference Systems gives a performance ranking of wheat flour products manufacturing systems. The first step is obtaining data to identify the failure modes from expert’s opinions. The second step is the fuzzification process to convert crisp input to a fuzzy set., then the IF-then fuzzy rule applied through inference engine, and in the final step, the defuzzification process is applied to convert the fuzzy output into real numbers.

Keywords: failure modes, fuzzy rules, fuzzy inference system, risk assessment

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Authors: Palanisamy Samyraj, Sriram Yogesh, Kishore Kumar, Vaishak Cibi

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The project is about design and analysis of crankshaft using Al-Al2O3 composite material. The project is mainly concentrated across two areas one is to design and analyze the composite material, and the other is to work on the practical model. Growing competition and the growing concern for the environment has forced the automobile manufactures to meet conflicting demands such as increased power and performance, lower fuel consumption, lower pollution emission and decrease noise and vibration. Metal matrix composites offer good properties for a number of automotive components. The work reports on studies on Al-Al2O3 as the possible alternative material for a crank shaft. These material have been considered for use in various components in engines due to the high amount of strength to weight ratio. These materials are significantly taken into account for their light weight, high strength, high specific modulus, low co-efficient of thermal expansion, good air resistance properties. In addition high specific stiffness, superior high temperature, mechanical properties and oxidation resistance of Al2O3 have developed some advanced materials that are Al-Al2O3 composites. Crankshafts are used in automobile industries. Crankshaft is connected to the connecting rod for the movement of the piston which is subjected to high stresses which cause the wear of the crankshaft. Hence using composite material in crankshaft gives good fuel efficiency, low manufacturing cost, less weight.

Keywords: metal matrix composites, Al-Al2O3, high specific modulus, strength to weight ratio

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Authors: Jigg Pelayo, Ricardo Villar

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Leaning on the development of aerial laser scanning in the Philippine geospatial industry, researches about remote sensing and machine vision technology became a trend. Object detection via template matching is one of its application which characterized to be fast and in real time. The paper purposely attempts to provide application for robust pattern matching algorithm based on the normalized cross correlation (NCC) criterion function subjected in Object-based image analysis (OBIA) utilizing high-resolution aerial imagery and low density LiDAR data. The height information from laser scanning provides effective partitioning order, thus improving the hierarchal class feature pattern which allows to skip unnecessary calculation. Since detection is executed in the object-oriented platform, mathematical morphology and multi-level filter algorithms were established to effectively avoid the influence of noise, small distortion and fluctuating image saturation that affect the rate of recognition of features. Furthermore, the scheme is evaluated to recognized the performance in different situations and inspect the computational complexities of the algorithms. Its effectiveness is demonstrated in areas of Misamis Oriental province, achieving an overall accuracy of 91% above. Also, the garnered results portray the potential and efficiency of the implemented algorithm under different lighting conditions.

Keywords: algorithm, LiDAR, object recognition, OBIA

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Authors: Mohsen Hajian Foroushani, Samane Maroufi, Rasoul Khayyam Nekouei, Veena Sahajwalla

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Lithium (Li) metal possesses outstanding characteristics, with the highest specific capacity (3860 mAh g-1) and the lowest electrochemical potential (-3.04 V vs. SHE) among available metal anodes. The collaborative impact of Li and sulfur, featuring a specific capacity of 1670 mAh g-1, positions Li–S batteries (LSBs) as highly promising contenders for the next generation of high-energy-density batteries. However, the comprehensive commercialization of LSBs relies on addressing various challenges inherent to these batteries. One of the most formidable hurdles is the widespread issue of Li dendrite nucleation and growth on the anode surface, stemming from the inherent instability of the solid electrolyte interphase (SEI) layer. In this study, we employed a Zn-based coating derived from waste materials, significantly enhancing the performance of the symmetrical cell across various current densities. The applied coating not only improved the cyclability of the cell by more than fourfold but also reduced the charge transfer resistance from over 300 to less than 10 before cycling. Examination through SEM micrographs of both samples revealed the successful suppression of Li dendrites by the applied coating.

Keywords: Li-S batteries, Li dendrite, sustainability, Li anode

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Authors: Yasmeen Saleem, Pedro Berliner, Nurit Agam

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The most severe limitation for plant production in arid areas is water. Rainfall events are rare but can have pulses of high intensity. As a result, crusts are formed, which decreases infiltration into the soil, and results additionally in erosive losses of soil. Direct evaporation of water from the wetted soil can account for large fractions of the water stored in the soil. Different kinds of mulches have been used to decrease the loss of water in arid and semi-arid region. This study aims to evaluate the effect of polystyrene styrofoam pellets mulch on soil infiltration, runoff, and evaporation as a more efficient and economically viable mulch alternative. Polystyrene styrofoam pellets of two sizes (0.5 and 1 cm diameter) will be placed on top of the soil in two mulch layer depths (1 and 2 cm), in addition to the non-mulched treatment. The rainfall simulator will be used as an artificial source of rain. The preliminary results in the prototype experiment indicate that polystyrene styrofoam pellets decreased runoff, increased soil-water infiltration. We are still testing the effect of these pellets on decreasing the soil-water evaporation.

Keywords: synthetic mulch, runoff, evaporation, infiltration

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Authors: Arth J. Shah, Madhu R. Kamble

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Voice biometric liveness detection is customized to certify an authentication process of the voice data presented is genuine and not a recording or synthetic voice. With the rise of deepfakes and other equivalently sophisticated spoofing generation techniques, it’s becoming challenging to ensure that the person on the other end is a live speaker or not. Voice Liveness Detection (VLD) system is a group of security measures which detect and prevent voice spoofing attacks. Motivated by the recent development of the Kolmogorov-Arnold Network (KAN) based on the Kolmogorov-Arnold theorem, we proposed KAN for the VLD task. To date, multilayer perceptron (MLP) based classifiers have been used for the classification tasks. We aim to capture not only the compositional structure of the model but also to optimize the values of univariate functions. This study explains the mathematical as well as experimental analysis of KAN for VLD tasks, thereby opening a new perspective for scientists to work on speech and signal processing-based tasks. This study emerges as a combination of traditional signal processing tasks and new deep learning models, which further proved to be a better combination for VLD tasks. The experiments are performed on the POCO and ASVSpoof 2017 V2 database. We used Constant Q-transform, Mel, and short-time Fourier transform (STFT) based front-end features and used CNN, BiLSTM, and KAN as back-end classifiers. The best accuracy is 91.26 % on the POCO database using STFT features with the KAN classifier. In the ASVSpoof 2017 V2 database, the lowest EER we obtained was 26.42 %, using CQT features and KAN as a classifier.

Keywords: Kolmogorov Arnold networks, multilayer perceptron, pop noise, voice liveness detection

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Authors: Saad M. Darwish, Magda M. Madbouly, Murad B. Khorsheed

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Sign Languages (SL) are the most accomplished forms of gestural communication. Therefore, their automatic analysis is a real challenge, which is interestingly implied to their lexical and syntactic organization levels. Hidden Markov models (HMM’s) have been used prominently and successfully in speech recognition and, more recently, in handwriting recognition. Consequently, they seem ideal for visual recognition of complex, structured hand gestures such as are found in sign language. In this paper, several results concerning static hand gesture recognition using an algorithm based on Type-2 Fuzzy HMM (T2FHMM) are presented. The features used as observables in the training as well as in the recognition phases are based on Singular Value Decomposition (SVD). SVD is an extension of Eigen decomposition to suit non-square matrices to reduce multi attribute hand gesture data to feature vectors. SVD optimally exposes the geometric structure of a matrix. In our approach, we replace the basic HMM arithmetic operators by some adequate Type-2 fuzzy operators that permits us to relax the additive constraint of probability measures. Therefore, T2FHMMs are able to handle both random and fuzzy uncertainties existing universally in the sequential data. Experimental results show that T2FHMMs can effectively handle noise and dialect uncertainties in hand signals besides a better classification performance than the classical HMMs. The recognition rate of the proposed system is 100% for uniform hand images and 86.21% for cluttered hand images.

Keywords: hand gesture recognition, hand detection, type-2 fuzzy logic, hidden Markov Model

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Authors: Nahed O. Bawakid, Walied M. Alarif

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With regard to the uniqueness of the red algae of the genus Laurencia as the source of C₁₅-acetogenins, along with the diversity of biological applications; the acetogenin content of the Red Sea L. obtusa was investigated. Fractionation and purification of the CH₂Cl₂/MeOH extract were done by applying several chromatographic techniques, including column and preparative thin-layer chromatography; followed by a series of ¹H nuclear magnetic resonance measurements to give rise of some interesting notes. A new rare chloroallene-based C₁₅ acetogenin, laurentusenin (1) along with a new furan ring containing C₁₅ acetogenin, laurenfuresenin (2), were isolated from the red alga L. obtusa. Comparing 1D and 2D NMR, MS, UV and IR spectral data for the new isolated compounds with the reported bromoallene containing acetogenins spectral data was played the crucial role for characterization of their hemical structures. The apoptosis induced by these two compounds was demonstrated by DNA fragmentation assay and microscopic observation. These observations suggest that (1) and (2) may be involved in regulation of programmed death in the initiation and propagation of inflammatory responses. The isolated metabolite (1) showed unusual substituted allene side chain, while (2) inserted furan ring as a new acetogenin nucleus.

Keywords: cyclic enyne, anti-inflammatory, fatty acids, marine algae, halogenations

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Authors: Prarthana Gowda, Tushar Sakorikar, Siva K. Reddy, Darim B. Ferry, Abha Misra

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Graphene, a two-dimensional carbon allotrope has demonstrated excellent electrical, mechanical and optical properties. A tunable band gap of grapheme demonstrated broad band absorption of light with a response time of picoseconds, however it suffers a fast recombination of the photo generated carriers. Many reports have explored to overcome this problem; in this presentation, we discuss defect induced enhanced photoresponse in a few layer graphene (FLG) due to exposure of infrared (IR) radiation. The two and four-fold enhancement in the photocurrent is achieved by addition of multiwalled carbon nano tubes (MWCNT) to an FLG surface and also creating the wrinkles in the FLG (WG) respectively. In our study, it is also inferred that the photo current generation is highly dependent on the morphological defects on the graphene. It is observed that the FLG (without defects) generates the photo current instantaneously, and after a prolonged exposure to the IR radiation decays the generation rate. Importantly, the presence of MWCNT on FLG enhances the stability and WG presented both stable as well as enhanced photo response.

Keywords: graphene, multiwalled carbon nano tubes, wrinkled graphene, photo detector, photo current

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Authors: Joy Shihyi Huang

Abstract:

This paper discusses the concept of community in Anna Deavere Smith’s performance, one that challenges and explores existing notions of justice and the other. In contrast to unwavering assumptions of essentialism that have helped to propel a discourse on moral agency within the black community, Smith employs postmodern ideas in which the theatrical attributes of doubling and repetition are conceptualized as part of what Marvin Carlson coined as a ‘memory machine.’ Her dismissal of the need for linear time, such as that regulated by Aristotle’s The Poetics and its concomitant ethics, values, and emotions as a primary ontological and epistemological construct produced by the existing African American historiography, demonstrates an urgency to produce an alternative communal self to override metanarratives in which the African Americans’ lives are contained and sublated by specific historical confines. Drawing on Emmanuel Levinas’ theories in ethics, specifically his notion of ‘proximity’ and ‘the third,’ the paper argues that Smith enacts a new model of ethics by launching an acting method that eliminates the boundary of self and other. Defying psychological realism, Smith conceptualizes an approach to acting that surpasses the mere mimetic value of invoking a ‘likeness’ of an actor to a character, which as such, resembles the mere attribution of various racial or sexual attributes in identity politics. Such acting, she contends, reduces the other to a representation of, at best, an ultimate rendering of me/my experience. She instead appreciates ‘unlikeness,’ recognizes the unavoidable actor/character gap as a power that humbles the self, whose irreversible journey to the other carves out its own image.

Keywords: Anna Deavere Smith, Emmanuel Levinas, other, performance

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Authors: Kemal Polat

Abstract:

In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.

Keywords: machine learning, data weighting, classification, data mining

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Authors: Ikram Kamal, Mohamed Blaghen

Abstract:

Pollution caused by petroleum hydrocarbons in terrestrial and aquatic environment is a common phenomenon that causes significant ecological and social problems. Biosurfactant applications in the environmental industries are promising due to their biodegradability, low toxicity and effectiveness in enhancing biodegradation and solubilization of low solubility compounds. Currently, the main application is for enhancement of oil recovery and hydrocarbon bioremediation due to their biodegradability and low critical micelle concentration (CMC). In this study we have investigated the potential of bacterial strains collected aseptically from the lagoon Marchika (water and soil) in Nador, Morocco; for the production of biosurfactants. This study also aimed to optimize the biosurfactant production process by changing the variables that influence the type and amount of biosurfactant produced by these microorganisms such as: carbon sources and also other physical and chemical parameters such as temperature and pH. Emulsification index, methylene blue test and thin layer chromatography (TLC) revealed the ability of strains used in this study to produce compounds that could emulsify gasoline. In addition a GC/MS was used to separate and identify different biosurfactants purified.

Keywords: petroleum hydrocarbons, biosurfactant, biodegradability, critical micelle concentration, lagoon Marchika

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Authors: Diala Bitar, Emmanuel Gourdon, Claude H. Lamarque, Manuel Collet

Abstract:

Acoustic absorber devices play an important role reducing the noise at the propagation and reception paths. An electroacoustic absorber consists of a loudspeaker coupled to an electric shunt circuit, where the membrane is playing the role of an absorber/reflector of sound. Although the use of linear shunt resistors at the transducer terminals, has shown to improve the performances of the dynamical absorbers, it is nearly efficient in a narrow frequency band. Therefore, and since nonlinear phenomena are promising for their ability to absorb the vibrations and sound on a larger frequency range, we propose to couple a nonlinear electric shunt circuit at the loudspeaker terminals. Then, the equivalent model can be described by a 2 degrees of freedom system, consisting of a primary linear oscillator describing the dynamics of the loudspeaker membrane, linearly coupled to a cubic nonlinear energy sink (NES). The system is analytically treated for the case of 1:1 resonance, using an invariant manifold approach at different time scales. The proposed methodology enables us to detect the equilibrium points and fold singularities at the first slow time scales, providing a predictive tool to design the nonlinear circuit shunt during the energy exchange process. The preliminary results are promising; a significant improvement of acoustic absorption performances are obtained.

Keywords: electroacoustic absorber, multiple-time-scale with small finite parameter, nonlinear energy sink, nonlinear passive shunt

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Authors: Mohamed El Morsy, Gabriela Achtenová

Abstract:

Research on damage of gears and gear pairs using vibration signals remains very attractive, because vibration signals from a gear pair are complex in nature and not easy to interpret. Predicting gear pair defects by analyzing changes in vibration signal of gears pairs in operation is a very reliable method. Therefore, a suitable vibration signal processing technique is necessary to extract defect information generally obscured by the noise from dynamic factors of other gear pairs. This article presents the value of cepstrum analysis in vehicle gearbox fault diagnosis. Cepstrum represents the overall power content of a whole family of harmonics and sidebands when more than one family of sidebands is present at the same time. The concept for the measurement and analysis involved in using the technique are briefly outlined. Cepstrum analysis is used for detection of an artificial pitting defect in a vehicle gearbox loaded with different speeds and torques. The test stand is equipped with three dynamometers; the input dynamometer serves as the internal combustion engine, the output dynamometers introduce the load on the flanges of the output joint shafts. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. Also, a method for fault diagnosis of gear faults is presented based on order cepstrum. The procedure is illustrated with the experimental vibration data of the vehicle gearbox. The results show the effectiveness of cepstrum analysis in detection and diagnosis of the gear condition.

Keywords: cepstrum analysis, fault diagnosis, gearbox, vibration signals

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Authors: Javed Y. Uppal

Abstract:

In this paper, a case study of a 13 storied multi storied main headquarters building of the Lahore Development Authority Lahore Pakistan has been presented, the 9th floor of which caught fire due to short circuiting and the flare spread through air-conditioning ducts to top three floors, and the building remained under fire for 15 hours before it was quenched. Some columns at the upper 3 floors started crumbling down, which were immediately propped. A visual inspection of site was first carried out, followed by onsite material tests and lab tests for residual strengths, which led to the decision of removal of the top 3 floors in a planned sequence of diamond cutting of middle strips, column strips, and shear walls, in panels and their lifting up by overhead cranes. The waffle slabs were stitched and jacketed with low viscosity polymer layer. The damaged bars were supplemented. The cracked columns were jacketed as well. The validity of rehabilitation procedure was established by load deflection behavior tests and long term performance observation over a period of 5 years. The paper concludes that the procedures adopted could be recommended for such events.

Keywords: fire damage, shotcrete, waffle slabs, delamination, drying cracking, jacketing

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Authors: K. H. Teng, A. Shaw, M. Ateeq, A. Al-Shamma'a, S. Wylie, S. N. Kazi, B. T. Chew

Abstract:

Numerical and experimental of using novel electromagnetic wave technique to detect water hardness concentration has been presented in this paper. Simulation is powerful and efficient engineering methods which allow for a quick and accurate prediction of various engineering problems. The RF module is used in this research to predict and design electromagnetic wave propagation and resonance effect of a guided wave to detect water hardness concentration in term of frequency domain, eigenfrequency, and mode analysis. A cylindrical cavity resonator is simulated and designed in the electric field of fundamental mode (TM010). With the finite volume method, the three-dimensional governing equations were discretized. Boundary conditions for the simulation were the cavity materials like aluminum, two ports which include transmitting and receiving port, and assumption of vacuum inside the cavity. The design model was success to simulate a fundamental mode and extract S21 transmission signal within 2.1 – 2.8 GHz regions. The signal spectrum under effect of port selection technique and dielectric properties of different water concentration were studied. It is observed that the linear increment of magnitude in frequency domain when concentration increase. The numerical results were validated closely by the experimentally available data. Hence, conclusion for the available COMSOL simulation package is capable of providing acceptable data for microwave research.

Keywords: electromagnetic wave technique, frequency domain, signal spectrum, water hardness concentration

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