Search results for: deep composite kernel

Authors: A. Zecchin, E. Vallicella, I. Alberi, A. Dalle Carbonare, A. Festi, F. Galeone, S. Garzon, R. Raffaelli, P. Pomini, M. Franchi

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Introduction: Severe endometriosis is a multiorgan disease, that involves bowel in 31% of cases. Disabling symptoms and deep infiltration can lead to bowel obstruction: surgical bowel treatment may be needed. In these cases, colorectal segment resection is usually performed by inferior mesenteric artery ligature, as radically as for oncological surgery. This study was made on surgery based on intestinal vascular axis’ preservation. It was assessed postoperative complications risks (mainly rate of dehiscence of intestinal anastomoses), and results were compared with the ones found in literature about classical colorectal resection. Materials and methods: This was a retrospective study based on 62 patients with deep infiltrating endometriosis of the bowel, which undergo segmental resection with intestinal vascular axis preservation, between 2013 and 2016. It was assessed complications related to the intervention both during hospitalization and 30-60 days after resection. Particular attention was paid to the presence of anastomotic dehiscence. 52 patients were finally telephonically interviewed in order to investigate the presence or absence of intestinal constipation. Results and Conclusion: Segmental intestinal resection performed in this study ensured a more conservative vascular approach, with lower rate of anastomotic dehiscence (1.6%) compared to classical literature data (10.0% to 11.4% ). No complications were observed regarding spontaneous recovery of intestinal motility and bladder emptying. Constipation in some patients, even after years of intervention, is not assessable in the absence of a preoperative constipation state assessment.

Keywords: anastomotic dehiscence, deep infiltrating endometriosis, colorectal resection, vascular axis preservation

Procedia PDF Downloads 188

Authors: Shaoying Guo, Yanyun Xu, Meng Zhang, Weiqing Huang

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The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.

Keywords: cross-validation support vector machine, refined com- posite multiscale dispersion entropy, specific emitter identification, transient signal, wireless communication device

Procedia PDF Downloads 119

Authors: Camila Hurtado, Maria A. Morales, Diego Torres, L.H. Reyes, Alejandro Maranon, Alicia Porras

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This work presents the physical and chemical characterization of beer brand fibers and the properties of novel composite materials made of these fibers and polylactic acid (PLA). Treated and untreated fibers were physically characterized in terms of their moisture content (ASTM D1348), density, and particle size (ASAE S319.2). A chemical analysis following TAPPI standards was performed to determine ash, extractives, lignin, and cellulose content on fibers. Thermal stability was determined by TGA analysis, and an FTIR was carried out to check the influence of the alkali treatment in fiber composition. An alkali treatment with NaOH (5%) of fibers was performed for 90 min, with the objective to improve the interfacial adhesion with polymeric matrix in composites. Composite materials based on either treated or untreated beer brand fibers and polylactic acid (PLA) were developed characterized in tension (ASTM D638), bending (ASTM D790) and impact (ASTM D256). Before composites manufacturing, PLA and brand beer fibers (10 wt.%) were mixed in a twin extruder with a temperature profile between 155°C and 180°C. Coupons were manufactured by compression molding (110 bar) at 190°C. Physical characterization showed that alkali treatment does not affect the moisture content (6.9%) and the density (0.48 g/cm³ for untreated fiber and 0.46 g/cm³ for the treated one). Chemical and FTIR analysis showed a slight decrease in ash and extractives. Also, a decrease of 47% and 50% for lignin and hemicellulose content was observed, coupled with an increase of 71% for cellulose content. Fiber thermal stability was improved with the alkali treatment at about 10°C. Tensile strength of composites was found to be between 42 and 44 MPa with no significant statistical difference between coupons with either treated or untreated fibers. However, compared to neat PLA, composites with beer bran fibers present a decrease in tensile strength of 27%. Young modulus increases by 10% with treated fiber, compared to neat PLA. Flexural strength decreases in coupons with treated fiber (67.7 MPa), while flexural modulus increases (3.2 GPa) compared to neat PLA (83.3 MPa and 2.8 GPa, respectively). Izod impact test results showed an improvement of 99.4% in coupons with treated fibers - compared with neat PLA.

Keywords: beer bran, characterization, green composite, polylactic acid, surface treatment

Procedia PDF Downloads 114

Authors: S. U. Durgadsimi, S. Chouguleb, S. Belladc

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(y) Li0.5Ni0.7Zn0.05Fe2O4 + (1-y) Ba0.5Sr0.5TiO3 magnetoelectric composites with y = 0.1, 0.3 and 0.5 were prepared by a conventional standard double sintering ceramic technique. X-ray diffraction analysis confirmed the phase formation of ferrite, ferroelectric and their composites. logρdc Vs 1/T graphs reveal that the dc resistivity decreases with increasing temperature exhibiting semiconductor behavior. The plots of logσac Vs logω2 are almost linear indicating that the conductivity increases with increase in frequency i.e, conductivity in the composites is due to small polaron hopping. Dielectric constant (έ) and dielectric loss (tan δ) were studied as a function of frequency in the range 100Hz–1MHz which reveals the normal dielectric behavior except the composite with y=0.1 and as a function of temperature at four fixed frequencies (i.e. 100Hz, 1KHz, 10KHz, 100KHz). ME voltage coefficient decreases with increase in ferrite content and was observed to be maximum of about 7.495 mV/cmOe for (0.1) Li0.5Ni0.7Zn0.05Fe2O4 + (0.9) Ba0.5Sr0.5TiO3 composite.

Keywords: XRD, dielectric constant, dielectric loss, DC and AC conductivity, ME voltage coefficient

Procedia PDF Downloads 330

Authors: Ying Han, Yuanxiang Chen, Yongtao Huang, Jia Fu, Kaile Li, Shangjing Lin, Jianguo Yu

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In long-haul and high-speed optical transmission system, the orthogonal frequency division multiplexing (OFDM) signal suffers various linear and non-linear impairments. In recent years, researchers have proposed compensation schemes for specific impairment, and the effects are remarkable. However, different impairment compensation algorithms have caused an increase in transmission delay. With the widespread application of deep neural networks (DNN) in communication, multi-impairment compensation based on DNN will be a promising scheme. In this paper, we propose and apply DNN to compensate multi-impairment of 16-QAM coherent optical OFDM signal, thereby improving the performance of the transmission system. The trained DNN models are applied in the offline digital signal processing (DSP) module of the transmission system. The models can optimize the constellation mapping signals at the transmitter and compensate multi-impairment of the OFDM decoded signal at the receiver. Furthermore, the models reduce the peak to average power ratio (PAPR) of the transmitted OFDM signal and the bit error rate (BER) of the received signal. We verify the effectiveness of the proposed scheme for 16-QAM Coherent Optical OFDM signal and demonstrate and analyze transmission performance in different transmission scenarios. The experimental results show that the PAPR and BER of the transmission system are significantly reduced after using the trained DNN. It shows that the DNN with specific loss function and network structure can optimize the transmitted signal and learn the channel feature and compensate for multi-impairment in fiber transmission effectively.

Keywords: coherent optical OFDM, deep neural network, multi-impairment compensation, optical transmission

Procedia PDF Downloads 129

Authors: John Eric C. Bargas, Maria Cecilia M. Marcos

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One of the most common ground improvement techniques is Deep Soil Mixing (DSM). As the technique progresses, there is still lack in the development when it comes to depth control. This was the issue experienced during the installation of DSM in one of the National projects in the Philippines. This study assesses the feasibility of using equipment drilling parameters such as hydraulic pressure, drilling speed and rotational speed in determining the Standard Penetration Test N-value of a specific soil. Hydraulic pressure and drilling speed with a constant rotational speed of 30 rpm have a positive correlation with SPT N-value for cohesive soil and sand. A linear trend was observed for cohesive soil. The correlation of SPT N-value and hydraulic pressure yielded a R²=0.5377 while the correlation of SPT N-value and drilling speed has a R²=0.6355. While the best fitted model for sand is polynomial trend. The correlation of SPT N-value and hydraulic pressure yielded a R²=0.7088 while the correlation of SPT N-value and drilling speed has a R²=0.4354. The low correlation may be attributed to the behavior of sand when the auger penetrates. Sand tends to follow the rotation of the auger rather than resisting which was observed for very loose to medium dense sand. Specific Energy and the product of hydraulic pressure and drilling speed yielded same R² with a positive correlation. Linear trend was observed for cohesive soil while polynomial trend for sand. Cohesive soil yielded a R²=0.7320 which has a strong relationship. Sand also yielded a strong relationship having a coefficient of determination, R²=0.7203. It is feasible to use hydraulic pressure and drilling speed to estimate the SPT N-value of the soil. Also, the product of hydraulic pressure and drilling speed can be a substitute to specific energy when estimating the SPT N-value of a soil. However, additional considerations are necessary to account for other influencing factors like ground water and physical and mechanical properties of soil.

Keywords: ground improvement, equipment drilling parameters, standard penetration test, deep soil mixing

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Authors: Dhaladhuli Pranavi, Amirtham Rajagopal

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There are various failure modes in ceramic matrix composites; notable ones are fiber breakage, matrix cracking and fiber matrix debonding. Crack nucleation and propagation in microstructure of such composites requires an understanding of interaction of crack with the multiple inclusion heterogeneous system and interfaces. In order to assess structural integrity, the material parameters especially of the interface that governs the crack growth should be determined. In the present work, a nonlocal phase field approach is proposed to model the crack interface interaction in such composites. Nonlocal approaches help in understanding the complex mechanisms of delamination growth and mitigation and operates at a material length scale. The performance of the proposed formulation is illustrated through representative numerical examples. The model proposed is implemented in the framework of the finite element method. Several parametric studies on interface crack interaction are conducted. The proposed model is easy and simple to implement and works very well in modeling fracture in composite systems.

Keywords: composite, interface, nonlocal, phase field

Procedia PDF Downloads 134

Authors: Nikoloz Jalabadze, Roin Chedia, Lili Nadaraia, Levan Khundadze

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Nanocrystalline materials in powder condition can be manufactured by a number of different methods, however manufacture of composite materials product in the same nanocrystalline state is still a problem because the processes of compaction and synthesis of nanocrystalline powders go with intensive growth of particles – the process which promotes formation of pieces in an ordinary crystalline state instead of being crystallized in the desirable nanocrystalline state. To date spark plasma sintering (SPS) has been considered as the most promising and energy efficient method for producing dense bodies of composite materials. An advantage of the SPS method in comparison with other methods is mainly low temperature and short time of the sintering procedure. That finally gives an opportunity to obtain dense material with nanocrystalline structure. Graphene has recently garnered significant interest as a reinforcing phase in composite materials because of its excellent electrical, thermal and mechanical properties. Graphene nanoplatelets (GNPs) in particular have attracted much interest as reinforcements for ceramic matrix composites (mostly in Al2O3, Si3N4, TiO2, ZrB2 a. c.). SPS has been shown to fully densify a variety of ceramic systems effectively including Al2O3 and often with improvements in mechanical and functional behavior. Alumina consolidated by SPS has been shown to have superior hardness, fracture toughness, plasticity and optical translucency compared to conventionally processed alumina. Knowledge of how GNPs influence sintering behavior is important to effectively process and manufacture process. In this study, the effects of GNPs on the SPS processing of Al2O3 are investigated by systematically varying sintering temperature, holding time and pressure. Our experiments showed that SPS process is also appropriate for the synthesis of nanocrystalline powders of alumina-graphene composites. Depending on the size of the molds, it is possible to obtain different amount of nanopowders. Investigation of the structure, physical-chemical, mechanical and performance properties of the elaborated composite materials was performed. The results of this study provide a fundamental understanding of the effects of GNP on sintering behavior, thereby providing a foundation for future optimization of the processing of these promising nanocomposite systems.

Keywords: alumina oxide, ceramic matrix composites, graphene nanoplatelets, spark-plasma sintering

Procedia PDF Downloads 363

Authors: Fatiha Teklal, Bachir Kacimi, Arezki Djebbar

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The study and application of composite materials are a truly interdisciplinary endeavor that has been enriched by contributions from chemistry, physics, materials science, mechanics and manufacturing engineering. The understanding of the interface (or interphase) in composites is the central point of this interdisciplinary effort. From the early development of composite materials of various nature, the optimization of the interface has been of major importance. Even more important, the ideas linking the properties of composites to the interface structure are still emerging. In our study, we need a direct characterization of the interface; the micromechanical tests we are addressing seem to meet this objective and we chose to use two complementary tests simultaneously. The microindentation test that can be applied to real composites and the drop test, preferred to the pull-out because of the theoretical possibility of studying systems with high adhesion (which is a priori the case with our systems). These two tests are complementary because of the principle of the model specimen used for both the first "compression indentation" and the second whose fiber is subjected to tensile stress called the drop test. Comparing the results obtained by the two methods can therefore be rewarding.

Keywords: Fiber, Interface, Matrix, Micromechanics, Pull-out

Procedia PDF Downloads 102

Authors: Seyedeh Bahar Hashemi, Alireza Rahimi, Mehdi Arjmand

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Food is the source of energy and growth through the breakdown of its vital components and plays a vital role in human health and nutrition. Many natural compounds found in plant and animal materials play a special role in biological systems and the origin of many such compounds directly or indirectly is algae. Algae is an enormous source of polysaccharides and have gained much interest in human flourishing. In this study, algae biomass extraction is conducted using deep eutectic-based solvents (NADES) and Ultrasound-assisted extraction (UAE). The aim of this research is to extract bioactive compounds including total carotenoid, antioxidant activity, and polyphenolic contents. For this purpose, the influence of three important extraction parameters namely, biomass-to-solvent ratio, temperature, and time are studied with respect to their impact on the recovery of carotenoids, and phenolics, and on the extracts’ antioxidant activity. Here we employ the Response Surface Methodology for the process optimization. The influence of the independent parameters on each dependent is determined through Analysis of Variance. Our results show that Ultrasound-assisted extraction (UAE) for 50 min is the best extraction condition, and proline:lactic acid (1:1) and choline chloride:urea (1:2) extracts show the highest total phenolic contents (50.00 ± 0.70 mgGAE/gdw) and antioxidant activity [60.00 ± 1.70 mgTE/gdw, 70.00 ± 0.90 mgTE/gdw in 2.2-diphenyl-1-picrylhydrazyl (DPPH), and 2.2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS)]. Our results confirm that the combination of UAE and NADES provides an excellent alternative to organic solvents for sustainable and green extraction and has huge potential for use in industrial applications involving the extraction of bioactive compounds from algae. This study is among the first attempts to optimize the effects of ultrasonic-assisted extraction, ultrasonic devices, and deep natural eutectic point and investigate their application in bioactive compounds extraction from algae. We also study the future perspective of ultrasound technology which helps to understand the complex mechanism of ultrasonic-assisted extraction and further guide its application in algae.

Keywords: natural deep eutectic solvents, ultrasound-assisted extraction, algae, antioxidant activity, phenolic compounds, carotenoids

Procedia PDF Downloads 158

Authors: Zakaria Ahmed, Khaled Charradi, Sherif M. A. S. Keshk, Radhouane Chtourou

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Sulfonated poly ether ether ketone (SPEEK) with a low sulfonation degree was blended using nanofiller Layered Double Hydroxide (LDH, Mg2AlCl) /sepiolite nanostructured material as additive to use as an electrolyte membrane for fuel cell application. Characterization assessments, i.e., mechanical stability, thermal gravimetric analysis, ion exchange capability, swelling properties, water uptake capacities, electrochemical impedance spectroscopy analysis, and Fourier transform infrared spectroscopy (FTIR) of the composite membranes were conducted. The presence of LDH/sepiolite nanoarchitecture material within SPEEK was found to have the highest water retention and proton conductivity value at high temperature rather than LDH/SPEEK and pristine SPEEK membranes.

Keywords: SPEEK, sepiolite clay, LDH clay, proton exchange membrane

Procedia PDF Downloads 108

Authors: J. S. S. Neto, R. A. A. Lima, D. K. K. Cavalcanti, J. P. B. Souza, R. A. A. Aguiar, M. D. Banea

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In the last decade, investments in sustainable processes and products have gained space in several segments, such as in the civil, automobile, textile and other industries. In addition to increasing concern about the development of environmentally friendly materials that reduce, energy costs and reduces environmental impact in the production of these products, as well as reducing CO2 emissions. Natural fibers offer a great alternative to replace synthetic fibers, totally or partially, because of their low cost and their renewable source. The purpose of this research is to study the effect of surface chemical treatment on the thermal properties of hybrid fiber reinforced natural fibers (NFRC), jute + ramie, jute + sisal, jute + curauá, and jute fiber in polymer matrices. Two types of chemical treatment: alkalinization and silanization were employed, besides the condition without treatment. Differential scanning calorimetry (DSC), thermogravimetry (TG) and dynamic-mechanical analysis (DMA) were performed to explore the thermal stability and weight loss in the natural fiber reinforced composite as a function of chemical treatment.

Keywords: chemical treatment, hybrid composite, jute, thermal

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Authors: Puneet Kumar, Jonnalagadda Srinivas

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The authors report here vibration and buckling analysis of functionally graded carbon nanotube-polymer composite (FG-CNTPC) beams under hygro-thermo-mechanical environments using higher order shear deformation theory. The material properties of CNT and polymer matrix are often affected by temperature and moisture content. A micromechanical model with agglomeration effect is employed to compute the elastic, thermal and moisture properties of the composite beam. The governing differential equation of FG-CNTRPC beam is developed using higher-order shear deformation theory to account shear deformation effects. The elastic, thermal and hygroscopic strain terms are derived from variational principles. Moreover, thermal and hygroscopic loads are determined by considering uniform, linear and sinusoidal variation of temperature and moisture content through the thickness. Differential equations of motion are formulated as an eigenvalue problem using appropriate displacement fields and solved by using finite element modeling. The obtained results of natural frequencies and critical buckling loads show a good agreement with published data. The numerical illustrations elaborate the dynamic as well as buckling behavior under uniaxial load for different environmental conditions, boundary conditions and volume fraction distribution profile, beam slenderness ratio. Further, comparisons are shown at different boundary conditions, temperatures, degree of moisture content, volume fraction as well as agglomeration of CNTs, slenderness ratio of beam for different shear deformation theories.

Keywords: hygrothermal effect, free vibration, buckling load, agglomeration

Procedia PDF Downloads 250

Authors: Semayat Fanta, P.M. Mohite, C.S. Upadhyay

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Damage meso-model for laminates is one of the most widely applicable approaches for the analysis of damage induced in laminated fiber-reinforced polymeric composites. Damage meso-model for laminates has been developed over the last three decades by many researchers in experimental, theoretical, and analytical methods that have been carried out in micromechanics as well as meso-mechanics analysis approaches. It has been fundamentally developed based on the micromechanical description that aims to predict the damage initiation and evolution until the failure of structure in various loading conditions. The current damage meso-model for laminates aimed to act as a bridge between micromechanics and macro-mechanics of the laminated composite structure. This model considers two meso-constituents for the analysis of damage in ply and interface that imparted from low-velocity impact. The damages considered in this study include fiber breakage, matrix cracking, and diffused damage of the lamina, and delamination of the interface. The damage initiation and evolution in laminae can be modeled in terms of damaged strain energy density using damage parameters and the thermodynamic irreversible forces. Interface damage can be modeled with a new concept of spherical micro-void in the resin-rich zone of interface material. The damage evolution is controlled by the damage parameter (d) and the radius of micro-void (r) from the point of damage nucleation to its saturation. The constitutive martial model for meso-constituents is defined in a user material subroutine VUMAT and implemented in ABAQUS/Explicit finite element modeling tool. The model predicts the damages in the meso-constituents level very accurately and is considered the most effective technique of modeling low-velocity impact simulation for laminated composite structures.

Keywords: mesomodel, laminate, low-energy impact, micromechanics

Procedia PDF Downloads 209

Authors: Pandiyarajan Thangaraj, Mangalaraja Ramalinga Viswanathan, Karthikeyan Balasubramanian, Héctor D. Mansilla, José Ruiz, David Contreras

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We report a systematic study of structural and optical properties of Pr-doped ZnO nanostructures and PVA:Zn98Pr2O polymer matrix nanocomposites free standing films are performed. These particles are synthesized through simple wet chemical route and solution casting technique at room temperature, respectively. Structural studies carried out by X-ray diffraction method, confirms that the prepared pure ZnO and Pr-doped ZnO nanostructures are in hexagonal wurtzite structure and the microstrain is increased upon doping. TEM analysis reveals that the prepared materials are in the sheet-like nature. Absorption spectra show free excitonic absorption band at 370 nm and red shift for the Pr-doped ZnO nanostructures. The PVA:Zn98Pr2O composite film exhibits both free excitonic and PVA absorption bands at 282 nm. Fourier transform infrared spectral studies confirm the presence of A1 (TO) and E1 (TO) modes of Zn-O bond vibration and the formation of polymer composite materials.

Keywords: Pr doped ZnO, polymer nanocomposites, optical properties, free standing film

Procedia PDF Downloads 457

Authors: Niloufar Yadgari

Abstract:

GANs are a potent form of deep learning models that have found success in various fields. They are part of the larger group of generative techniques, which aim to produce authentic data using a probabilistic model that learns distributions from actual samples. In clinical settings, GANs have demonstrated improved abilities in capturing spatially intricate, nonlinear, and possibly subtle disease impacts in contrast to conventional generative techniques. This review critically evaluates the current research on how GANs are being used in imaging studies of different neurological conditions like Alzheimer's disease, brain tumors, aging of the brain, and multiple sclerosis. We offer a clear explanation of different GAN techniques for each use case in neuroimaging and delve into the key hurdles, unanswered queries, and potential advancements in utilizing GANs in this field. Our goal is to connect advanced deep learning techniques with neurology studies, showcasing how GANs can assist in clinical decision-making and enhance our comprehension of the structural and functional aspects of brain disorders.

Keywords: GAN, pathology, generative adversarial network, neuro imaging

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Authors: Hamed Khosravi, Reza Eslami-Farsani

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Increased interest in lightweight and efficient structural components has created the need for selecting materials with improved mechanical properties. To do so, composite materials are being widely used in many applications, due to durability, high strength and modulus, and low weight. Among the various composite structures, grid-stiffened structures are extensively considered in various aerospace and aircraft applications, because of higher specific strength and stiffness, higher impact resistance, superior load-bearing capacity, easy to repair, and excellent energy absorption capability. Although there are a good number of publications on the design aspects and fabrication of grid structures, little systematic work has been reported on their material modification to improve their properties, to our knowledge. Therefore, the aim of this research is to study the reinforcing effect of silica nanoparticles on the flexural properties of epoxy/E-glass isogrid panels under three-point bending test. Samples containing 0, 1, 3, and 5 wt.% of the silica nanoparticles, with 44 and 48 vol.% of the glass fibers in the ribs and skin components respectively, were fabricated by using a manual filament winding method. Ultrasonic and mechanical routes were employed to disperse the nanoparticles within the epoxy resin. To fabricate the ribs, the unidirectional fiber rovings were impregnated with the matrix mixture (epoxy + nanoparticles) and then laid up into the grooves of a silicone mold layer-by-layer. At once, four plies of woven fabrics, after impregnating into the same matrix mixture, were layered on the top of the ribs to produce the skin part. In order to conduct the ultimate curing and to achieve the maximum strength, the samples were tested after 7 days of holding at room temperature. According to load-displacement graphs, the bellow trend was observed for all of the samples when loaded from the skin side; following an initial linear region and reaching a load peak, the curve was abruptly dropped and then showed a typical absorbed energy region. It would be worth mentioning that in these structures, a considerable energy absorption was observed after the primary failure related to the load peak. The results showed that the flexural properties of the nanocomposite samples were always higher than those of the nanoparticle-free sample. The maximum enhancement in flexural maximum load and energy absorption was found to be for the incorporation of 3 wt.% of the nanoparticles. Furthermore, the flexural stiffness was continually increased by increasing the silica loading. In conclusion, this study suggested that the addition of nanoparticles is a promising method to improve the flexural properties of grid-stiffened fibrous composite structures.

Keywords: grid-stiffened composite structures, nanocomposite, three point flexural test , energy absorption

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Authors: R. M. EL-Sharkawy, L. S. Nasrat, K. B. Ewiss

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This work presents a study of flashover voltage for outdoor polyester and composite insulators under dry, ultra-violet and contaminated conditions. Cylindrical of polyester composite samples (with different lengths) have been prepared after incorporated with different concentration of inorganic filler e.g. Magnesium Hydroxide [Mg(OH)2] to improve the electrical and thermal properties in addition to maximize surface flashover voltage and decrease tracking phenomena. Results showed that flashover voltage reaches to 46 kV for samples without filler and 52.6 kV for samples containing 40% of [Mg(OH)2] filler in dry condition. A comparison between different concentrations of filler under various environmental conditions (dry and contaminated conditions) showed higher flashover voltage values for samples containing filler with ratio 40% [Mg(OH)2] and length 3cm than that of samples containing filler [Mg(OH)2] with ratios 20%, 30% and lengths 0.5cm, 1cm, 2cm and 2.5cm. Flashover voltage decreases by adding [Mg(OH)2] filler for polyester samples under ultra-violet condition; as the ratio of filler increases, the value of flashover voltage decreases Also, in this study, the effect of thermal performance with respect to surface of the sample under test have been investigated in details.

Keywords: flashover voltage, filler, polymers, ultra-violet radiation

Procedia PDF Downloads 305

Authors: Kun Qi, Yuman Zhou, Jianxin He

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A facile fabrication strategy via electrospinning and followed by in situ polymerization to fabricate a highly stretchable and conductive Poly(3,4-ethylenedioxythiophene)/Polyurethane (PEDOT/PU) nanofibrous membrane is reported. PU nanofibers were prepared by electrospinning and then PEDOT was coated on the plasma modified PU nanofiber surface via in-situ polymerization to form flexible PEDOT/PU composite nanofibers with conductivity. The results show PEDOT is successfully synthesized on the surface of PU nanofiber and PEDOT/PU composite nanofibers possess skin-core structure. Furthermore, the experiments indicate the optimal technological parameters of the polymerization process are as follow: The concentration of EDOT monomers is 50 mmol/L, the polymerization time is 24 h and the temperature is 25℃. The PEDOT/PU nanofibers exhibit excellent electrical conductivity ( 27.4 S/cm). In addition, flexible sensor made from conductive PEDOT/PU nanofibers shows highly sensitive response towards tensile strain and also can be used to detect finger motion. The results demonstrate promising application of the as-obtained nanofibrous membrane in flexible wearable electronic fields.

Keywords: electrospinning, polyurethane, PEDOT, conductive nanofiber, flexible senor

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Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

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With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: document processing, framework, formal definition, machine learning

Procedia PDF Downloads 199

Authors: Halimatu S. Abdullahi, Ray E. Sheriff, Fatima Mahieddine

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Agriculture is essential to the continuous existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Technology can aid/improve agriculture in several ways through pre-planning and post-harvest by the use of computer vision technology through image processing to determine the soil nutrient composition, right amount, right time, right place application of farm input resources like fertilizers, herbicides, water, weed detection, early detection of pest and diseases etc. This is precision agriculture which is thought to be solution required to achieve our goals. There has been significant improvement in the area of image processing and data processing which has being a major challenge. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetations need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used to determine soil nutrients required in a plantation for maximum production. The experimental results on the developed model yielded results with an average accuracy of 99.58%.

Keywords: convolution, feature extraction, image analysis, validation, precision agriculture

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Authors: Yunwei Zhang, Na Li, Yuhong Niu

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Bone tissue engineering scaffold was regarded as an important clinical technology of curing bony defect. The patent protection of bone tissue engineering scaffold had been paid more attention and strengthened all over the world. This study analyzed the future development trends of international technologies in the field of bone tissue engineering scaffold and its patent protection. This study used the methods of data classification and classification indexing to analyze 2718 patents retrieved in the patent database. Results showed that the patents coming from United States had a competitive advantage over other countiries in the field of bone tissue engineering scaffold. The number of patent applications by a single company in U.S. was a quarter of that of the world. However, the capability of R&D in China was obviously weaker than global level, patents mainly coming from universities and scientific research institutions. Moreover, it would be predicted that synthetic organic materials as new materials would be gradually replaced by composite materials. The patent technology protections of composite materials would be more strengthened in the future.

Keywords: bone tissue engineering, patent analysis, Scaffold material, patent protection

Procedia PDF Downloads 124

Authors: Sarah Pasala, Elizabeth Zacharias

Abstract:

Vital sign monitoring is crucial for both everyday health and medical diagnosis. A significant factor in assessing a human's health is their vital signs, which include heart rate, breathing rate, blood pressure, and electrocardiogram (ECG) readings. Vital sign monitoring has been the focus of many system and method innovations recently. Piezoelectrics are materials that convert mechanical energy into electrical energy and can be used for vital sign monitoring. Piezoelectric energy harvesters that are stretchable and flexible can detect very low frequencies like airflow, heartbeat, etc. Current advancements in piezoelectric materials and flexible sensors have made it possible to create wearable and implantable medical devices that can continuously monitor physiological signals in humans. But because of their non-biocompatible nature, they also produce a large amount of e-waste and require another surgery to remove the implant. This paper presents a biocompatible and flexible piezoelectric composite material for wearable and implantable devices that offers a high-performance platform for seamless and continuous monitoring of human physiological signals and tactile stimuli. It also addresses the issue of e-waste and secondary surgery. A Lead-free piezoelectric, SrBi4Ti4O15, is found to be suitable for this application because the properties can be tailored by suitable substitutions and also by varying the synthesis temperature protocols. In the present work, SrBi4Ti4O15 modified by rare-earth has been synthesized and studied. Coupling factors are calculated from resonant (fr) and anti-resonant frequencies (fa). It is observed that Samarium substitution in SBT has increased the Curie temperature, dielectric and piezoelectric properties. From impedance spectroscopy studies, relaxation, and non-Debye type behaviour are observed. The composite of bioresorbable poly(l-lactide) and Lead-free rare earth modified Bismuth Layered Ferroelectrics leads to a flexible piezoelectric device for non-invasive measurement of vital signs, such as heart rate, breathing rate, blood pressure, and electrocardiogram (ECG) readings and also artery pulse signals in near-surface arteries. These composites are suitable to detect slight movement of the muscles and joints. This Lead-free rare earth modified Bismuth Layered Ferroelectrics – polymer composite is synthesized using a ball mill and the solid-state double sintering method. XRD studies indicated the two phases in the composite. SEM studies revealed the grain size to be uniform and in the range of 100 nm. The electromechanical coupling factor is improved. The elastic constants are calculated and the mechanical flexibility is found to be improved as compared to the single-phase rare earth modified Bismuth Latered piezoelectric. The results indicate that this composite is suitable for the non-invasive detection of multiple vital signs of humans.

Keywords: composites, flexible, non-invasive, piezoelectric

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Authors: Hossam Abdelrahman, Sama Rostom, Reem Yassein, Yara Mohamed, Salma Salah, Nour Awny

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In today’s environment, people are becoming increasingly interested in their appearance. However, they are afraid of their unknown appearance after a plastic surgery or treatment. Accidents, burns and genetic problems such as bowing of body parts of people have a negative impact on their mental health with their appearance and this makes them feel uncomfortable and underestimated. The approach presents a revolutionary deep learning-based image inpainting method that analyses the various picture structures and corrects damaged images. In this study, A model is proposed based on the in-painting of medical images with Stable Diffusion Inpainting method. Reconstructing missing and damaged sections of an image is known as image inpainting is a key progress facilitated by deep neural networks. The system uses the input of the user of an image to indicate a problem, the system will then modify the image and output the fixed image, facilitating for the patient to see the final result.

Keywords: generative adversarial network, large mask inpainting, stable diffusion inpainting, plastic surgery

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Authors: Mustafa Albayrak, Mete Onur Kaman, Ilyas Bozkurt

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In this study, the necessary material parameters were determined to be able to conduct progressive damage analysis of layered composites under low velocity impact by using the MAT162 material module in the LS-DYNA program. The material module MAT162 based on Hashin failure criterion requires 34 parameters in total. Some of these parameters were obtained directly as a result of dynamic and quasi-static mechanical tests, and the remaining part was calibrated and determined by comparing numerical and experimental results. Woven glass/epoxy was used as the composite material and it was produced by vacuum infusion method. In the numerical model, composites are modeled as three-dimensional and layered. As a result, the acquisition of MAT162 material module parameters, which will enable progressive damage analysis, is given in detail and step by step, and the selection methods of the parameters are explained. Numerical data consistent with the experimental results are given in graphics.

Keywords: Composite Impact, Finite Element Simulation, Progressive Damage Analyze, LS-DYNA, MAT162

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Authors: Shi Qi Koo, Ahmad Beng Hong Kueh

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In the present work, the finite element formulation for the investigation of the effects of a localized interfacial degeneration on the dynamic behavior of the [90˚/0˚] laminated composite plate employing the state-space technique is performed. The stiffness of the laminate is determined by assembling the stiffnesses of sub-elements. This includes an introduction of an interface layer adopting the virtually zero-thickness formulation to model the interfacial degeneration. Also, the kinematically consistent mass matrix and proportional damping have been formulated to complete the free vibration governing expression. To simulate the interfacial degeneration of the laminate, the degenerated areas are defined from the center propagating outwards in a localized manner. It is found that the natural frequency, damped frequency and damping ratio of the plate decreases as the degenerated area of the interface increases. On the contrary, the loss factor increases correspondingly.

Keywords: dynamic finite element, localized interface degeneration, proportional damping, state-space modeling

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Authors: G. Farkas, K. Mathis, J. Pilch, P. Minarik

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Deformation mechanisms in an Mg-Al-Ca alloy reinforced with short alumina fibres were studied by acoustic emission and in-situ neutron diffraction method. The fibres plane orientation with respect to the loading axis was found to be a key parameter, which influences the acting deformation processes, such as twinning or dislocation slip. In-situ neutron diffraction tests were measured at different temperatures from room temperature (RT) to 200°C. The measurement shows the lattice strain changes in the matrix and also in the reinforcement phase depending on macroscopic compressive deformation and stress. In case of parallel fibre plane orientation, the increment of compressive lattice strain is lower in the matrix and higher in the fibres in comparison to perpendicular fibre orientation. Furthermore, acoustic emission results indicate a larger twinning activity and more frequent fibre cracking in sample with perpendicular fibre plane orientation. Both types of mechanisms are more dominant at elevated temperatures.

Keywords: neutron diffraction, acoustic emission, magnesium based composite, deformation mechanisms

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Authors: Marija Milašinović-Šeremešić, Valentina Semenčenko, Milica Radosavljević, Dušanka Terzić, Ljiljana Mojović, Ljubica Dokić

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Maize (Zea mays L.) is one of the most important cereal crops, and as such, one of the most significant naturally renewable carbohydrate raw materials for the production of energy and multitude of different products. The main goal of the present study was to investigate a suitability of selected maize hybrids of different genetic background produced in Maize Research Institute ‘Zemun Polje’, Belgrade, Serbia, for starch, bioethanol and animal feed production. All the hybrids are commercial and their detailed characterization is important for the expansion of their different uses. The starches were isolated by using a 100-g laboratory maize wet-milling procedure. Hydrolysis experiments were done in two steps (liquefaction with Termamyl SC, and saccharification with SAN Extra L). Starch hydrolysates obtained by the two-step hydrolysis of the corn flour starch were subjected to fermentation by S. cerevisiae var. ellipsoideus under semi-anaerobic conditions. The digestibility based on enzymatic solubility was performed by the Aufréré method. All investigated ZP maize hybrids had very different physical characteristics and chemical composition which could allow various possibilities of their use. The amount of hard (vitreous) and soft (floury) endosperm in kernel is considered one of the most important parameters that can influence the starch and bioethanol yields. Hybrids with a lower test weight and density and a greater proportion of soft endosperm fraction had a higher yield, recovery and purity of starch. Among the chemical composition parameters only starch content significantly affected the starch yield. Starch yields of studied maize hybrids ranged from 58.8% in ZP 633 to 69.0% in ZP 808. The lowest bioethanol yield of 7.25% w/w was obtained for hybrid ZP 611k and the highest by hybrid ZP 434 (8.96% w/w). A very significant correlation was determined between kernel starch content and the bioethanol yield, as well as volumetric productivity (48h) (r=0.66). Obtained results showed that the NDF, ADF and ADL contents in the whole maize plant of the observed ZP maize hybrids varied from 40.0% to 60.1%, 18.6% to 32.1%, and 1.4% to 3.1%, respectively. The difference in the digestibility of the dry matter of the whole plant among hybrids (ZP 735 and ZP 560) amounted to 18.1%. Moreover, the differences in the contents of the lignocelluloses fraction affected the differences in dry matter digestibility. From the results it can be concluded that genetic background of the selected maize hybrids plays an important part in estimation of the technological value of maize hybrids for various purposes. Obtained results are of an exceptional importance for the breeding programs and selection of potentially most suitable maize hybrids for starch, bioethanol and animal feed production.

Keywords: bioethanol, biomass quality, maize, starch

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Authors: Yaxin Bi

Abstract:

Accurate prediction and understanding of the evolution mechanisms of earthquakes remain challenging in the fields of geology, geophysics, and seismology. This study leverages Long Short-Term Memory (LSTM) networks and Generative Adversarial Networks (GANs), a generative model tailored to time-series data, for generating synthetic time series data based on Swarm satellite data, which will be used for detecting seismic anomalies. LSTMs demonstrated commendable predictive performance in generating synthetic data across multiple countries. In contrast, the GAN models struggled to generate synthetic data, often producing non-informative values, although they were able to capture the data distribution of the time series. These findings highlight both the promise and challenges associated with applying deep learning techniques to generate synthetic data, underscoring the potential of deep learning in generating synthetic electromagnetic satellite data.

Keywords: LSTM, GAN, earthquake, synthetic data, generative AI, seismic precursors

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Authors: R. M. S. Sachini Amararathne

Abstract:

This research is striving to develop a thermo degradable starch plastic compound/ masterbatch for industrial packaging applications. A native corn starch-modified with an esterification reaction of lauric acid is melt blent with an unsaturated elastomer (styrene-butadiene-rubber/styrene-butadiene-styrene). A trace amount of metal salt is added into the internal mixer to study the effect of pro-oxidants in a thermo oxidative environment. Then the granulated polymer composite which is consisted with 80-86% of polyolefin (LLDP/LDPE/PP) as the pivotal agent; is extruded with processing aids, antioxidants and some other additives in a co-rotating twin-screw extruder. The pelletized composite is subjected to compression molding/ Injection molding or blown film extrusion processes to acquire the samples/specimen for tests. The degradation process is explicated by analyzing the results of fourier transform infrared spectroscopy (FTIR) measurements, thermo oxidative aging studies (placing the dumb-bell specimen in an air oven at 70 °C for four weeks of exposure.) governed by tensile and impact strength test reports. Furthermore, the samples were elicited into manifold outdoors to inspect the degradation process. This industrial process is implemented to reduce the volume of fossil-based garbage by achieving the biodegradability and compostability in the natural cycle. Hence the research leads to manufacturing a degradable plastic packaging compound which is now available in the Sri Lankan market.

Keywords: blown film extrusion, compression moulding, polyolefin, pro-oxidant, styrene-butadine-rubber, styrene-butadiene-styrene, thermo oxidative aging, unsaturated elastomer

Procedia PDF Downloads 86