Search results for: residual LSTM
471 Particle Size Effect on Shear Strength of Granular Materials in Direct Shear Test
Authors: R. Alias, A. Kasa, M. R. Taha
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The effect of particle size on shear strength of granular materials are investigated using direct shear tests. Small direct shear test (60 mm by 60 mm by 24 mm deep) were conducted for particles passing the sieves with opening size of 2.36 mm. Meanwhile, particles passing the standard 20 mm sieves were tested using large direct shear test (300 mm by 300 mm by 200 mm deep). The large direct shear tests and the small direct shear tests carried out using the same shearing rate of 0.09 mm/min and similar normal stresses of 100, 200, and 300 kPa. The results show that the peak and residual shear strength decreases as particle size increases.Keywords: particle size, shear strength, granular material, direct shear test
Procedia PDF Downloads 479470 Biosorption of Heavy Metals from Aqueous Solutions by Plant Biomass
Authors: Yamina Zouambia, Khadidja Youcef Ettoumi, Mohamed Krea, Nadji Moulai Mostefa
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Environment pollution through various wastes (particularly by heavy metals) is a major environmental problem due to industrialization and the development of various human activities. Considerable attention has been focused, in recent years, upon the field of biosorption which represents a biotechnological innovation as well as an excellent tool for removal of metal ions from aqueous effluents. So the purpose of this study is to valorize by-product which are orange peels and an extract of these peels (pectin; a heteropolysaccharide) in treatment of water containing heavy metals. All biosorption experiments were carried out at room temperature, an indicated pH, a precise amount of biosorbent and under continuous stirring. Biosorption kinetic was determined by evaluating the residual concentration of the metal ion at different time intervals using UV spectroscopy. The results obtained show that the orange peels and pectin are interesting biosorbents with maximum biosorption capacity of up to 140 mg/g.Keywords: orange peels, pectin, heavy metals, biosorption
Procedia PDF Downloads 329469 Recurrent Neural Networks for Complex Survival Models
Authors: Pius Marthin, Nihal Ata Tutkun
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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)
Procedia PDF Downloads 81468 Empirical Evaluation of Gradient-Based Training Algorithms for Ordinary Differential Equation Networks
Authors: Martin K. Steiger, Lukas Heisler, Hans-Georg Brachtendorf
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Deep neural networks and their variants form the backbone of many AI applications. Based on the so-called residual networks, a continuous formulation of such models as ordinary differential equations (ODEs) has proven advantageous since different techniques may be applied that significantly increase the learning speed and enable controlled trade-offs with the resulting error at the same time. For the evaluation of such models, high-performance numerical differential equation solvers are used, which also provide the gradients required for training. However, whether classical gradient-based methods are even applicable or which one yields the best results has not been discussed yet. This paper aims to redeem this situation by providing empirical results for different applications.Keywords: deep neural networks, gradient-based learning, image processing, ordinary differential equation networks
Procedia PDF Downloads 154467 Experimental Study on Ultrasonic Shot Peening Forming and Surface Properties of AALY12
Authors: Shi-hong Lu, Chao-xun Liu, Yi-feng Zhu
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Ultrasonic shot peening (USP) on AALY12 sheet was studied. Several parameters (arc heights, surface roughness, surface topography and microhardness) with different USP process parameters were measured. The research proposes that the radius of curvature of shot peened sheet increases with time and electric current decreasing, while it increases with pin diameter increasing, and radius of curvature reaches a saturation level after a specific processing time and electric current. An empirical model of the relationship between radius of curvature and pin diameter, electric current, time was also obtained. The research shows that the increment of surface and vertical microhardness of material is more obvious with longer time and higher value of electric current, which can be up to 20% and 28% respectively.Keywords: USP forming, surface properties, radius of curvature, residual stress
Procedia PDF Downloads 514466 Cells Detection and Recognition in Bone Marrow Examination with Deep Learning Method
Authors: Shiyin He, Zheng Huang
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In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet
Procedia PDF Downloads 178465 Mutational Analysis of JAK2V617F in Tunisian CML Patients with TKI-Resistance
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Background:Chronicmyeloidleukemia (CML), a hematologicaldisease, ischaracterized by t (9; 22) and relatedoncogene BCR-ABL formation. Although Tyrosine kinase inhibitors (TKIs) have revolutionized the treatment of CML, resistanceoccurs and possibly médiates by mutation in severalgenesindependently of the bcr-abl1 kinase mechanism. it has been reportedthat JAK2V617F/BCR-ABL double positivitymaybe a potential marker of resistance in CML. Aims: This studywasinvestigated the JAK2V617F mutation in TKI-resistant CML patients. Methods: A retrospectivestudywasconducted in the Hospital University of Sfax, south of Tunisia, including all CML TKI-resistant patients. A Sanger sequencingwasperformedusing a high-fidelity DNA polymerase. Results:Nineresistant CP-CML patients wereenrolled in thisstudy. The JAK2V617F mutation wasdetectedin 3 patients with TKI resistance. Conclusion:Despite the limit of ourstudy, ourfinding highlights the high frequency of JAK2V617F/BCR-ABL double positivity as an important marker of resistance. So; the combination of JAK and TKI inhibitorsmightbe effective and potentiallybeguided by molecular monitoring of minimal residual disease1.Keywords: chronic myeloid leukemia, tyrosine kinase inhibitors, resistance, JAK2V617F, BCR-ABL
Procedia PDF Downloads 61464 A Review on the Use of Plastic Waste with Viable Materials in Composite Construction Block
Authors: Mohan T. Harish, Masson Lauriane, Sreevalsa Kolathayar
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Environmental issues raise alarm in the constructional field which implies a need for exploring new construction materials derived from the waste and residual products. This paper presents a detailed review of the alternatives approaches employed in the construction field using plastic waste in mixture with mixed with fillers. A detailed analysis of the plastic waste used in concrete, with soil, sand, clay and natural residues like sawdust, rice husk etc are presented. The different process carried forward was also discussed along with the scrutiny of the change in mechanical properties. The effect of coupling agents in the proposed mixture has been appraised in detail which gives implications for its future application in the field of plastic waste with viable materials in composite construction blocks.Keywords: plastic waste, composite materials, construction block, concrete, natural residue, coupling agent
Procedia PDF Downloads 245463 Synthesis of Dispersion-Compensating Triangular Lattice Index-Guiding Photonic Crystal Fibers Using the Directed Tabu Search Method
Authors: F. Karim
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In this paper, triangular lattice index-guiding photonic crystal fibers (PCFs) are synthesized to compensate the chromatic dispersion of a single mode fiber (SMF-28) for an 80 km optical link operating at 1.55 µm, by using the directed tabu search algorithm. Hole-to-hole distance, circular air-hole diameter, solid-core diameter, ring number and PCF length parameters are optimized for this purpose. Three Synthesized PCFs with different physical parameters are compared in terms of their objective functions values, residual dispersions and compensation ratios.Keywords: triangular lattice index-guiding photonic crystal fiber, dispersion compensation, directed tabu search, synthesis
Procedia PDF Downloads 421462 Undrained Shear Strength and Anisotropic Yield Surface of Diatomaceous Mudstone
Authors: Najibullah Arsalan, Masaru Akaishi, Motohiro Sugiyama
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When constructing a structure on soft rock, adequate research and study are required concerning the shear behavior in the over-consolidation region because soft rock is considered to be in a heavily over-consolidated state. In many of the existing studies concerning the strength of soft rock, triaxial compression tests were conducted using isotropically consolidated samples. In this study, the strength of diatomaceous soft rock anisotropically consolidated under a designated consolidation pressure is examined in undrained triaxial compression tests, and studies are made of the peak and residual strengths of the sample in the over-consolidated state in the initial yield surface and the anisotropic yield surface.Keywords: diatomaceouse mudstone, shear strength, yield surface, triaxial compression test
Procedia PDF Downloads 426461 Modelling and Simulation of Biomass Pyrolysis
Authors: P. Ahuja, K. S. S. Sai Krishna
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There is a concern over the energy shortage in the modern societies as it is one of the primary necessities. Renewable energy, mainly biomass, is found to be one feasible solution as it is inexhaustible and clean energy source all over the world. Out of various methods, thermo chemical conversion is considered to be the most common and convenient method to extract energy from biomass. The thermo-chemical methods that are employed are gasification, liquefaction and combustion. On gasification biomass yields biogas, on liquefaction biomass yields bio-oil and on combustion biomass yields bio-char. Any attempt to biomass gasification, liquefaction or combustion calls for a good understanding of biomass pyrolysis. So, Irrespective of the method used the first step towards the thermo-chemical treatment of biomass is pyrolysis. Pyrolysis mainly converts the solid mass into liquid with gas and residual char as the byproducts. Liquid is used for the production of heat, power and many other chemicals whereas the gas and char can be used as fuels to generate heat.Keywords: biomass, fluidisation, pyrolysis, simulation
Procedia PDF Downloads 334460 Aftershock Collapse Capacity Assessment of Mid-Rise Steel Moment Frames Subjected to As-Recorded Mainshock-Aftershock
Authors: Mohammadmehdi Torfehnejada, Serhan Senso
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Aftershock collapse capacity of Special Steel Moment Frames (SSMFs) is evaluated under aftershock earthquakes by considering building heights 8 and 12 stories. The assessment evaluates the residual collapse capacity under aftershock excitation when various levels of damage have been induced by the mainshock. For this purpose, incremental dynamic analysis (IDA) under aftershock follows the mainshock imposing the intended damage level. The study results indicate that aftershock collapse capacity of this structure may decrease remarkably when the structure is subjected to large mainshock damage. The capacity reduction under aftershock is finally related to the mainshock damage level through regression equations.Keywords: aftershock collapse capacity, special steel moment frames, mainshock-aftershock sequences, incremental dynamic analysis, mainshock damage
Procedia PDF Downloads 149459 A Case Study on Machine Learning-Based Project Performance Forecasting for an Urban Road Reconstruction Project
Authors: Soheila Sadeghi
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In construction projects, predicting project performance metrics accurately is essential for effective management and successful delivery. However, conventional methods often depend on fixed baseline plans, disregarding the evolving nature of project progress and external influences. To address this issue, we introduce a distinct approach based on machine learning to forecast key performance indicators, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category within an urban road reconstruction project. Our proposed model leverages time series forecasting techniques, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance by analyzing historical data and project progress. Additionally, the model incorporates external factors, including weather patterns and resource availability, as features to improve forecast accuracy. By harnessing the predictive capabilities of machine learning, our performance forecasting model enables project managers to proactively identify potential deviations from the baseline plan and take timely corrective measures. To validate the effectiveness of the proposed approach, we conduct a case study on an urban road reconstruction project, comparing the model's predictions with actual project performance data. The outcomes of this research contribute to the advancement of project management practices in the construction industry by providing a data-driven solution for enhancing project performance monitoring and control.Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, schedule variance, earned value management
Procedia PDF Downloads 31458 Examinations of Sustainable Protection Possibilities against Granary Weevil (Sitophilus granarius L.) on Stored Products
Authors: F. Pal-Fam, R. Hoffmann, S. Keszthelyi
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Granary weevil, Sitophilus granarius (L.) (Col.: Curculionidae) is a typical cosmopolitan pest. It can cause significant damage to stored grains, and can drastically decrease yields. Damaged grain has reduced nutritional and market value, weaker germination, and reduced weight. The commonly used protectants against stored-product pests in Europe are residual insecticides, applied directly to the product. Unfortunately, these pesticides can be toxic to mammals, the residues can accumulate in the treated products, and many pest species could become resistant to the protectants. During recent years, alternative solutions of grain protection have received increased attention. These solutions are considered as the most promising alternatives to residual insecticides. The aims of our comparative study were to obtain information about the efficacies of the 1. diatomaceous earth, 2. sterile insect technology and 3. herbal oils against the S. granarius on grain (foremost maize), and to evaluate the influence of the dose rate on weevil mortality and progeny. The main results of our laboratory experiments are the followings: 1. Diatomaceous earth was especially efficacious against S. granarius, but its insecticidal properties depend on exposure time and applied dose. The efficacy on barley was better than on maize. Mortality value of the highest dose was 85% on the 21st day in the case of barley. It can be ascertained that complete elimination of progeny was evidenced on both gain types. To summarize, a satisfactory efficacy level was obtained only on barley at a rate of 4g/kg. Alteration of efficacy between grain types can be explained with differences in grain surface. 2. The mortality consequences of Roentgen irradiation on the S. granarius was highly influenced by the exposure time, and the dose applied. At doses of 50 and 70Gy, the efficacy accepted in plant protection (mortality: 95%) was recorded only on the 21st day. During the application of 100 and 200Gy doses, high mortality values (83.5% and 97.5%) were observed on the 14th day. Our results confirmed the complete sterilizing effect of the doses of 70Gy and above. The autocide effect of 50 and 70Gy doses were demonstrated when irradiated specimens were mixed into groups of fertile specimens. Consequently, these doses might be successfully applied to put sterile insect technique (SIT) into practice. 3. The results revealed that both studied essential oils (Callendula officinalis, Hippophae rhamnoides) exerted strong toxic effect on S. granarius, but C. officinalis triggered higher mortality. The efficacy (94.62 ± 2.63%) was reached after a 48 hours exposure to H. rhamnoides oil at 2ml/kg while the application of 2ml/kg of C. officinalis oil for 24 hours produced 98.94 ± 1.00% mortality rate. Mortality was 100% at 5 ml/kg of H. rhamnoides after 24 hours duration of its application, while with C. officinalis the same value could be reached after a 12 hour-exposure to the oil. Both essential oils applied were eliminated the progeny.Keywords: Sitophilus granarius, stored product, protection, alternative solutions
Procedia PDF Downloads 166457 Electro-Hydrodynamic Effects Due to Plasma Bullet Propagation
Authors: Panagiotis Svarnas, Polykarpos Papadopoulos
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Atmospheric-pressure cold plasmas continue to gain increasing interest for various applications due to their unique properties, like cost-efficient production, high chemical reactivity, low gas temperature, adaptability, etc. Numerous designs have been proposed for these plasmas production in terms of electrode configuration, driving voltage waveform and working gas(es). However, in order to exploit most of the advantages of these systems, the majority of the designs are based on dielectric-barrier discharges (DBDs) either in filamentary or glow regimes. A special category of the DBD-based atmospheric-pressure cold plasmas refers to the so-called plasma jets, where a carrier noble gas is guided by the dielectric barrier (usually a hollow cylinder) and left to flow up to the atmospheric air where a complicated hydrodynamic interplay takes place. Although it is now well established that these plasmas are generated due to ionizing waves reminding in many ways streamer propagation, they exhibit discrete characteristics which are better mirrored on the terms 'guided streamers' or 'plasma bullets'. These 'bullets' travel with supersonic velocities both inside the dielectric barrier and the channel formed by the noble gas during its penetration into the air. The present work is devoted to the interpretation of the electro-hydrodynamic effects that take place downstream of the dielectric barrier opening, i.e., in the noble gas-air mixing area where plasma bullet propagate under the influence of local electric fields in regions of variable noble gas concentration. Herein, we focus on the role of the local space charge and the residual ionic charge left behind after the bullet propagation in the gas flow field modification. The study communicates both experimental and numerical results, coupled in a comprehensive manner. The plasma bullets are here produced by a custom device having a quartz tube as a dielectric barrier and two external ring-type electrodes driven by sinusoidal high voltage at 10 kHz. Helium gas is fed to the tube and schlieren photography is employed for mapping the flow field downstream of the tube orifice. Mixture mass conservation equation, momentum conservation equation, energy conservation equation in terms of temperature and helium transfer equation are simultaneously solved, leading to the physical mechanisms that govern the experimental results. Namely, we deal with electro-hydrodynamic effects mainly due to momentum transfer from atomic ions to neutrals. The atomic ions are left behind as residual charge after the bullet propagation and gain energy from the locally created electric field. The electro-hydrodynamic force is eventually evaluated.Keywords: atmospheric-pressure plasmas, dielectric-barrier discharges, schlieren photography, electro-hydrodynamic force
Procedia PDF Downloads 134456 Bleaching Liquor Recovery of Batch-Wise and Continuous Method
Authors: Sidra Saleemi, Arsalan Khan, Urooj Baig, Tahir Jamil
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In this research, it was examined that some residual amount of bleaching chemicals left in the liquor, this amount is more in Batch-wise process as compared to continuous process. These chemicals can be recovered and reused for bleaching by adding more quantity of fresh bleaching chemicals and water, this quantity will be required to balance the recipe for fabric. This liquor is recovered and samples were bleached with different modified recipe of liquor for both processes i.e. Batch-wise and continuous process. Every time good results were achieved with negligible variation in the quality parameter between the fabric bleached with fresh liquor and the fabric bleached with Recovered Liquor. Additionally, samples were dyed, and found that dyeing can be done easily on samples bleached with recover liquor.Keywords: bleaching process, hydrogen peroxide, sodium hydroxide, liquor recovery
Procedia PDF Downloads 351455 Application of Waterflooding to the Kashkari Oil Field in Northern Afghanistan
Authors: Zabihullah Mahdi, Mahdi Nayab, Sadaf Jalal, Navid Seddiqi
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Hydrocarbons represent an important natural resource for the rehabilitation and sustainable development of Afghanistan. In this paper, the use of waterflooding is demonstrated for the petroleum reservoirs of the Kashkari oil field in northern Afghanistan. The technique is based on the Buckley–Leverett frontal-displacement theory, which enables computation of the progress of the waterfront in the reservoir. The relative permeabilities of oil and water, the residual oil saturation, and the irreducible water saturation are obtained from a laboratory experiment. The technique is applied to the laboratory plane-reservoir model to investigate the displacement mechanism and is then compared with the theoretical calculation. Lastly, the technique is applied to the Kashkari oil field to predict the feasible amount of oil that could be produced from this reservoir.Keywords: Buckley–Leverett, waterflooding, petroleum reservoir engineering, two-phase flow, immiscible displacement, porous media, relative permeability
Procedia PDF Downloads 187454 An Introduction to the Radiation-Thrust Based on Alpha Decay and Spontaneous Fission
Authors: Shiyi He, Yan Xia, Xiaoping Ouyang, Liang Chen, Zhongbing Zhang, Jinlu Ruan
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As the key system of the spacecraft, various propelling system have been developing rapidly, including ion thrust, laser thrust, solar sail and other micro-thrusters. However, there still are some shortages in these systems. The ion thruster requires the high-voltage or magnetic field to accelerate, resulting in extra system, heavy quantity and large volume. The laser thrust now is mostly ground-based and providing pulse thrust, restraint by the station distribution and the capacity of laser. The thrust direction of solar sail is limited to its relative position with the Sun, so it is hard to propel toward the Sun or adjust in the shadow.In this paper, a novel nuclear thruster based on alpha decay and spontaneous fission is proposed and the principle of this radiation-thrust with alpha particle has been expounded. Radioactive materials with different released energy, such as 210Po with 5.4MeV and 238Pu with 5.29MeV, attached to a metal film will provides various thrust among 0.02-5uN/cm2. With this repulsive force, radiation is able to be a power source. With the advantages of low system quantity, high accuracy and long active time, the radiation thrust is promising in the field of space debris removal, orbit control of nano-satellite array and deep space exploration. To do further study, a formula lead to the amplitude and direction of thrust by the released energy and decay coefficient is set up. With the initial formula, the alpha radiation elements with the half life period longer than a hundred days are calculated and listed. As the alpha particles emit continuously, the residual charge in metal film grows and affects the emitting energy distribution of alpha particles. With the residual charge or extra electromagnetic field, the emitting of alpha particles performs differently and is analyzed in this paper. Furthermore, three more complex situations are discussed. Radiation element generating alpha particles with several energies in different intensity, mixture of various radiation elements, and cascaded alpha decay are studied respectively. In combined way, it is more efficient and flexible to adjust the thrust amplitude. The propelling model of the spontaneous fission is similar with the one of alpha decay, which has a more complex angular distribution. A new quasi-sphere space propelling system based on the radiation-thrust has been introduced, as well as the collecting and processing system of excess charge and reaction heat. The energy and spatial angular distribution of emitting alpha particles on unit area and certain propelling system have been studied. As the alpha particles are easily losing energy and self-absorb, the distribution is not the simple stacking of each nuclide. With the change of the amplitude and angel of radiation-thrust, orbital variation strategy on space debris removal is shown and optimized.Keywords: alpha decay, angular distribution, emitting energy, orbital variation, radiation-thruster
Procedia PDF Downloads 199453 Web Data Scraping Technology Using Term Frequency Inverse Document Frequency to Enhance the Big Data Quality on Sentiment Analysis
Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan
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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis
Procedia PDF Downloads 81452 The Effect of Soil-Structure Interaction on the Post-Earthquake Fire Performance of Structures
Authors: A. T. Al-Isawi, P. E. F. Collins
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The behaviour of structures exposed to fire after an earthquake is not a new area of engineering research, but there remain a number of areas where further work is required. Such areas relate to the way in which seismic excitation is applied to a structure, taking into account the effect of soil-structure interaction (SSI) and the method of analysis, in addition to identifying the excitation load properties. The selection of earthquake data input for use in nonlinear analysis and the method of analysis are still challenging issues. Thus, realistic artificial ground motion input data must be developed to certify that site properties parameters adequately describe the effects of the nonlinear inelastic behaviour of the system and that the characteristics of these parameters are coherent with the characteristics of the target parameters. Conversely, ignoring the significance of some attributes, such as frequency content, soil site properties and earthquake parameters may lead to misleading results, due to the misinterpretation of required input data and the incorrect synthesise of analysis hypothesis. This paper presents a study of the post-earthquake fire (PEF) performance of a multi-storey steel-framed building resting on soft clay, taking into account the effects of the nonlinear inelastic behaviour of the structure and soil, and the soil-structure interaction (SSI). Structures subjected to an earthquake may experience various levels of damage; the geometrical damage, which indicates the change in the initial structure’s geometry due to the residual deformation as a result of plastic behaviour, and the mechanical damage which identifies the degradation of the mechanical properties of the structural elements involved in the plastic range of deformation. Consequently, the structure presumably experiences partial structural damage but is then exposed to fire under its new residual material properties, which may result in building failure caused by a decrease in fire resistance. This scenario would be more complicated if SSI was also considered. Indeed, most earthquake design codes ignore the probability of PEF as well as the effect that SSI has on the behaviour of structures, in order to simplify the analysis procedure. Therefore, the design of structures based on existing codes which neglect the importance of PEF and SSI can create a significant risk of structural failure. In order to examine the criteria for the behaviour of a structure under PEF conditions, a two-dimensional nonlinear elasto-plastic model is developed using ABAQUS software; the effects of SSI are included. Both geometrical and mechanical damages have been taken into account after the earthquake analysis step. For comparison, an identical model is also created, which does not include the effects of soil-structure interaction. It is shown that damage to structural elements is underestimated if SSI is not included in the analysis, and the maximum percentage reduction in fire resistance is detected in the case when SSI is included in the scenario. The results are validated using the literature.Keywords: Abaqus Software, Finite Element Analysis, post-earthquake fire, seismic analysis, soil-structure interaction
Procedia PDF Downloads 119451 Efficient Video Compression Technique Using Convolutional Neural Networks and Generative Adversarial Network
Authors: P. Karthick, K. Mahesh
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Video has become an increasingly significant component of our digital everyday contact. With the advancement of greater contents and shows of the resolution, its significant volume poses serious obstacles to the objective of receiving, distributing, compressing, and revealing video content of high quality. In this paper, we propose the primary beginning to complete a deep video compression model that jointly upgrades all video compression components. The video compression method involves splitting the video into frames, comparing the images using convolutional neural networks (CNN) to remove duplicates, repeating the single image instead of the duplicate images by recognizing and detecting minute changes using generative adversarial network (GAN) and recorded with long short-term memory (LSTM). Instead of the complete image, the small changes generated using GAN are substituted, which helps in frame level compression. Pixel wise comparison is performed using K-nearest neighbours (KNN) over the frame, clustered with K-means, and singular value decomposition (SVD) is applied for each and every frame in the video for all three color channels [Red, Green, Blue] to decrease the dimension of the utility matrix [R, G, B] by extracting its latent factors. Video frames are packed with parameters with the aid of a codec and converted to video format, and the results are compared with the original video. Repeated experiments on several videos with different sizes, duration, frames per second (FPS), and quality results demonstrate a significant resampling rate. On average, the result produced had approximately a 10% deviation in quality and more than 50% in size when compared with the original video.Keywords: video compression, K-means clustering, convolutional neural network, generative adversarial network, singular value decomposition, pixel visualization, stochastic gradient descent, frame per second extraction, RGB channel extraction, self-detection and deciding system
Procedia PDF Downloads 179450 ARABEX: Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder and Custom Convolutional Recurrent Neural Network
Authors: Hozaifa Zaki, Ghada Soliman
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In this paper, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder (ARABEX) with bidirectional LSTM. This approach is used for translating the Arabic dot-matrix expiration dates into their corresponding filled-in dates. A custom lightweight Convolutional Recurrent Neural Network (CRNN) model is then employed to extract the expiration dates. Due to the lack of available dataset images for the Arabic dot-matrix expiration date, we generated synthetic images by creating an Arabic dot-matrix True Type Font (TTF) matrix to address this limitation. Our model was trained on a realistic synthetic dataset of 3287 images, covering the period from 2019 to 2027, represented in the format of yyyy/mm/dd. We then trained our custom CRNN model using the generated synthetic images to assess the performance of our model (ARABEX) by extracting expiration dates from the translated images. Our proposed approach achieved an accuracy of 99.4% on the test dataset of 658 images, while also achieving a Structural Similarity Index (SSIM) of 0.46 for image translation on our dataset. The ARABEX approach demonstrates its ability to be applied to various downstream learning tasks, including image translation and reconstruction. Moreover, this pipeline (ARABEX+CRNN) can be seamlessly integrated into automated sorting systems to extract expiry dates and sort products accordingly during the manufacturing stage. By eliminating the need for manual entry of expiration dates, which can be time-consuming and inefficient for merchants, our approach offers significant results in terms of efficiency and accuracy for Arabic dot-matrix expiration date recognition.Keywords: computer vision, deep learning, image processing, character recognition
Procedia PDF Downloads 78449 Recovery of Boron as Homogeneous Perborate Particles from Synthetic Wastewater by Integrating Chemical Oxo-Precipitation with Fluidized-Bed Homogeneous Granulation
Authors: Chiung-Chin Huang, Jui-Yen Lin, Yao-Hui Huang
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Among current techniques of boron removal from wastewater with high boron concentration, chemical oxo-precipitation (COP) is one of the promising methods due to its milder condition. COP uses H2O2 to transform boric acid to perborates which can easily precipitate with barium ions at room temperature. However, the generation of the waste sludge that requires sludge/water separation and sludge dewatering is troublesome. This work presents an innovative technology which integrates chemical oxo-precipitation (COP) with fluidized-bed homogeneous granulation (FBHG) to reclaim boron as homogeneous perborate particles. By conducting COP in a fluidized-bed reactor, the barium perborate can be granulated to form homogeneous particles (>1.0 mm) with low water content (< 10%). Under the suitable condition, more than 70% of boron can be recovered from 600 ppm of boron solution and the residual boron is lower than 100 ppm.Keywords: barium, perborate, chemical oxo-precipitation, boron removal, fluidized-bed, granulation
Procedia PDF Downloads 315448 Fault Diagnosis of Squirrel-Cage Induction Motor by a Neural Network Multi-Models
Authors: Yahia. Kourd, N. Guersi D. Lefebvre
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In this paper we propose to study the faults diagnosis in squirrel-cage induction motor using MLP neural networks. We use neural healthy and faulty models of the behavior in order to detect and isolate some faults in machine. In the first part of this work, we have created a neural model for the healthy state using Matlab and a motor located in LGEB by acquirins data inputs and outputs of this engine. Then we detected the faults in the machine by residual generation. These residuals are not sufficient to isolate the existing faults. For this reason, we proposed additive neural networks to represent the faulty behaviors. From the analysis of these residuals and the choice of a threshold we propose a method capable of performing the detection and diagnosis of some faults in asynchronous machines with squirrel cage rotor.Keywords: faults diagnosis, neural networks, multi-models, squirrel-cage induction motor
Procedia PDF Downloads 627447 Numerical Investigation of Incompressible Turbulent Flows by Method of Characteristics
Authors: Ali Atashbar Orang, Carlo Massimo Casciola
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A novel numerical approach for the steady incompressible turbulent flows is presented in this paper. The artificial compressibility method (ACM) is applied to the Reynolds Averaged Navier-Stokes (RANS) equations. A new Characteristic-Based Turbulent (CBT) scheme is developed for the convective fluxes. The well-known Spalart–Allmaras turbulence model is employed to check the effectiveness of this new scheme. Comparing the proposed scheme with previous studies, it is found that the present CBT scheme demonstrates accurate results, high stability and faster convergence. In addition, the local time stepping and implicit residual smoothing are applied as the convergence acceleration techniques. The turbulent flows past a backward facing step, circular cylinder, and NACA0012 hydrofoil are studied as benchmarks. Results compare favorably with those of other available schemes.Keywords: incompressible turbulent flow, method of characteristics, finite volume, Spalart–Allmaras turbulence model
Procedia PDF Downloads 407446 Characterisation of the Physical Properties of Debris and Residual Soils Implications for the Possible Landslides Occurrence on Cililin West Java
Authors: Ikah Ning Prasetiowati Permanasari, Gunawan Handayani, Lilik Hendrajaya
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Landslide occurence at Mukapayung, Cililin West Java with material movement downward slope as far as 500m and hit residential areas of the village Nagrog cause eighteen people died and ten homes were destroyed and twenty-three heads of families evacuated. In order to test the hypothesis that soil at the landslides area is prone to landslides, we do drilling and the following tests were taken: particle size distribution, atterberg limits, shear strength, density, shringkage limits and triaxial unconsolidated and consolidated undrained test. Factor of safety was calculated to find out the possibility of subsequent landslides. The value of FOS of three layers is 1,05 which means that the soil in a critical condition and would be imminent to slide if there is disruption from the outside.Keywords: atterberg limits, particle size distribution, shear strength parameters, slope geometry, factor of safety
Procedia PDF Downloads 147445 The Investigation of Cracking on the Shell of Dryers (tag No. 2DR-1745 and DR-1402) in Shahid Tondguyan Petrochemical Company (STPC)
Authors: Ali Haghiri
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This research has been to investigate the cause of the stress corrosion cracking on dryer equipment (2DR-1745 and DR-1402) in Shahid Tondguyan Petrochemical Company (STPC). These dryers are as a drying powder Terphetalic acid in CTA2 and CTA1 unit. After passing through RVF equipment, wet cake moisture content of about 14% and temperature of 90C changed into a dry cake with a moisture content of less than 0.1% and the final temperature of about 140C and sent out Final Silo (FS-1820). After the declaration of the operation department concerning the observation of acid leakage under the primary insulation was decided that at the first opportunity, this issue must be investigated. So, after the shutdown of a unit at the date 2012/10/20 (2DR-1745) and 2021/11/24 (DR-1402) and after washing the dryer wall, insulation around the wall opened and it was found to crack and leakage from some points.Keywords: stress corrosion cracking, residual stress, austenitic stainless steel, Br- ion
Procedia PDF Downloads 151444 The Effect of H2S on Crystal Structure
Authors: C. Venkataraman B. E., J. Nagarajan B. E., V. Srinivasan M. Tech
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For a better understanding on sulfide stress corrosion cracking, a theoretical approach based on crystal structure, molecule behavior, flow of electrons and electrochemical reaction is developed. Its impact on different materials such as carbon steel, low alloy, alloy for sour (H2S) environments is studied. This paper describes the theories on various disaster and failures occurred in the industry by Stress Corrosion Cracking (SCC). Parameters such as pH of process fluid, partial pressure of CO2, O2, Chlorine, effect of internal pressure (crystal structure deformation by stress), and external environment condition are considered. An analytical line graph is then created for process fluid parameter verses time, temperature, induced/residual stress due to local pressure build-up. By comparison with the load test result of NACE and ASTM, it is possible to predict and simplify the control of SCC by use of materials like ferritic, Austenitic material in the oil and gas & petroleum industries.Keywords: crystal structure deformation, failure assessment, alloy-environment combination, H2S
Procedia PDF Downloads 397443 Experimental Chip/Tool Temperature FEM Model Calibration by Infrared Thermography: A Case Study
Authors: Riccardo Angiuli, Michele Giannuzzi, Rodolfo Franchi, Gabriele Papadia
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Temperature knowledge in machining is fundamental to improve the numerical and FEM models used for the study of some critical process aspects, such as the behavior of the worked material and tool. The extreme conditions in which they operate make it impossible to use traditional measuring instruments; infrared thermography can be used as a valid measuring instrument for temperature measurement during metal cutting. In the study, a large experimental program on superduplex steel (ASTM A995 gr. 5A) cutting was carried out, the relevant cutting temperatures were measured by infrared thermography when certain cutting parameters changed, from traditional values to extreme ones. The values identified were used to calibrate a FEM model for the prediction of residual life of the tools. During the study, the problems related to the detection of cutting temperatures by infrared thermography were analyzed, and a dedicated procedure was developed that could be used during similar processing.Keywords: machining, infrared thermography, FEM, temperature measurement
Procedia PDF Downloads 177442 Robust Diagnosis of an Electro-Mechanical Actuators, Bond Graph LFT Approach
Authors: A. Boulanoir, B. Ould Bouamama, A. Debiane, N. Achour
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The paper deals with robust Fault Detection and isolation with respect to parameter uncertainties based on linear fractional transformation form (LFT) Bond graph. The innovative interest of the proposed methodology is the use only one representation for systematic generation of robust analytical redundancy relations and adaptive residual thresholds for sensibility analysis. Furthermore, the parameter uncertainties are introduced graphically in the bond graph model. The methodology applied to the nonlinear industrial Electro-Mechanical Actuators (EMA) used in avionic systems, has determined first the structural monitorability analysis (which component can be monitored) with given instrumentation architecture with any need of complex calculation and secondly robust fault indicators for online supervision.Keywords: bond graph (BG), electro mechanical actuators (EMA), fault detection and isolation (FDI), linear fractional transformation (LFT), mechatronic systems, parameter uncertainties, avionic system
Procedia PDF Downloads 343