Search results for: deep composite kernel

Authors: Alona Faktor

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In this work, we present a NN-based computational model that can perform attention shifts according to high-level instruction. The instruction specifies the type of attentional shift using explicit geometrical relation. The instruction also can be of cognitive nature, specifying more complex human-human interaction or human-object interaction, or object-object interaction. Applying this approach sequentially allows obtaining a structural description of an image. A novel data-set of interacting humans and objects is constructed using a computer graphics engine. Using this data, we perform systematic research of relational segmentation shifts.

Keywords: cognitive science, attentin, deep learning, generalization

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Authors: Fiorenzo Lenzi, Doris Abt, Besnik Bytyqi

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Recent developments in composite materials for the interior cabin market provide more sustainable solutions for industrial applications. One contribution comes from epoxy-based prepregs recently developed to substitute phenolic prepregs in order to reduce the environmental impact of their production process and to eliminate health and safety issues related to their handling. Another example is the use of Mica-based products for improving the fire protection of interior cabin parts. Minerals, such as Mica, can be used as reinforcement in composites to reduce the heat release rate or, more traditionally, to improve the burn-through performance of fuselage and cargo lining components.

Keywords: prepreg, epoxy, Mica, battery protection

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Authors: Isahakyan Heghine

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Intertextuality, being in the centre of attention of both linguists and literary critics, is vividly expressed in the outstanding British novelist and philosopher J. Fowles' works. 'The Magus’ is a deep psychological and philosophical novel with vivid intertextual links with the Greek mythology and authors from different epochs. The aim of the paper is to show how intertextuality might serve as a dialogue between two authors (J. Fowles and J. Donne) disguised in the dialogue of two protagonists of the novel : Conchis and Nicholas. Contrastive viewpoints concerning man's isolation, loneliness are stated in the dialogue. Due to the conceptual analysis of the text it becomes possible both to decode the conceptual information of the text and find out its intertextual links.

Keywords: dialogue, conceptual analysis, isolation, intertextuality

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Authors: Moustafa Osman Mohammed

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Construction industry, as one of the main contributor in depletion of natural resources, influences climate change. This paper discusses incremental and evolutionary development of the proposed models for optimization of a life-cycle analysis to explicit strategy for evaluation systems. The main categories are virtually irresistible for introducing uncertainties, uptake composite structure model (CSM) as environmental management systems (EMSs) in a practice science of evaluation small and medium-sized enterprises (SMEs). The model simplified complex systems to reflect nature systems’ input, output and outcomes mode influence “framework measures” and give a maximum likelihood estimation of how elements are simulated over the composite structure. The traditional knowledge of modeling is based on physical dynamic and static patterns regarding parameters influence environment. It unified methods to demonstrate how construction systems ecology interrelated from management prospective in procedure reflects the effect of the effects of engineering systems to ecology as ultimately unified technologies in extensive range beyond constructions impact so as, - energy systems. Sustainability broadens socioeconomic parameters to practice science that meets recovery performance, engineering reflects the generic control of protective systems. When the environmental model employed properly, management decision process in governments or corporations could address policy for accomplishment strategic plans precisely. The management and engineering limitation focuses on autocatalytic control as a close cellular system to naturally balance anthropogenic insertions or aggregation structure systems to pound equilibrium as steady stable conditions. Thereby, construction systems ecology incorporates engineering and management scheme, as a midpoint stage between biotic and abiotic components to predict constructions impact. The later outcomes’ theory of environmental obligation suggests either a procedures of method or technique that is achieved in sustainability impact of construction system ecology (SICSE), as a relative mitigation measure of deviation control, ultimately.

Keywords: sustainability, environmental impact assessment, environemtal management, construction ecology

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Authors: Rakesh Dogra, Arun Kumar, Arvind Kumar Sharma

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This paper reports the thermoluminescence as well as optical properties of rare earth doped lithium fluoride (LiF) nanophosphor, synthesized via chemical route. The rare earth impurities (Yb and Sm) have been observed to increase the deep trap center capacity, which, in turn, enhance the radiation resistance of the LiF. This suggests the viability of these materials to be used as high dose thermoluminescent detectors at high temperature. Further, optical absorption measurements revealed the formation of radiation induced stable color centers in LiF at room temperature, which are independent of the rare earth dopant.

Keywords: lithium flouride, thermoluminescence, UV-VIS spectroscopy, Gamma radiations

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Authors: Qianwei Cheng, A. K. M. Mahbubur Rahman, Anis Sarker, Abu Bakar Siddik Nayem, Ovi Paul, Amin Ahsan Ali, M. Ashraful Amin, Ryosuke Shibasaki, Moinul Zaber

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Thomas Friedman, in his famous book, argued that the world in this 21st century is flat and will continue to be flatter. This is attributed to rapid globalization and the interdependence of humanity that engendered tremendous in-flow of human migration towards the urban spaces. In order to keep the urban environment sustainable, policy makers need to plan based on extensive analysis of the urban environment. With the advent of high definition satellite images, high resolution data, computational methods such as deep neural network analysis, and hardware capable of high-speed analysis; urban planning is seeing a paradigm shift. Legacy data on urban environments are now being complemented with high-volume, high-frequency data. However, the first step of understanding urban space lies in useful categorization of the space that is usable for data collection, analysis, and visualization. In this paper, we propose a pragmatic categorization method that is readily usable for machine analysis and show applicability of the methodology on a developing world setting. Categorization to plan sustainable urban spaces should encompass the buildings and their surroundings. However, the state-of-the-art is mostly dominated by classification of building structures, building types, etc. and largely represents the developed world. Hence, these methods and models are not sufficient for developing countries such as Bangladesh, where the surrounding environment is crucial for the categorization. Moreover, these categorizations propose small-scale classifications, which give limited information, have poor scalability and are slow to compute in real time. Our proposed method is divided into two steps-categorization and automation. We categorize the urban area in terms of informal and formal spaces and take the surrounding environment into account. 50 km × 50 km Google Earth image of Dhaka, Bangladesh was visually annotated and categorized by an expert and consequently a map was drawn. The categorization is based broadly on two dimensions-the state of urbanization and the architectural form of urban environment. Consequently, the urban space is divided into four categories: 1) highly informal area; 2) moderately informal area; 3) moderately formal area; and 4) highly formal area. In total, sixteen sub-categories were identified. For semantic segmentation and automatic categorization, Google’s DeeplabV3+ model was used. The model uses Atrous convolution operation to analyze different layers of texture and shape. This allows us to enlarge the field of view of the filters to incorporate larger context. Image encompassing 70% of the urban space was used to train the model, and the remaining 30% was used for testing and validation. The model is able to segment with 75% accuracy and 60% Mean Intersection over Union (mIoU). In this paper, we propose a pragmatic categorization method that is readily applicable for automatic use in both developing and developed world context. The method can be augmented for real-time socio-economic comparative analysis among cities. It can be an essential tool for the policy makers to plan future sustainable urban spaces.

Keywords: semantic segmentation, urban environment, deep learning, urban building, classification

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Authors: Pu Ying-Chih, Yang Yin-Ju, Hang Jian-Yi, Jang Guang-Way

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Organic-Inorganic hybrid materials consisting of graded distributions of inorganic nano particles in organic polymer matrices were successfully prepared by the sol-gel process. Optical and surface properties of the resulting nano composites can be manipulated by changing their compositions and nano particle distribution gradients. Applications of gradient nano composite materials include sealants for LED packaging and screen lenses for smartphones. Optical transparency, prism coupler, TEM, SEM, Energy Dispersive X-ray Spectrometer (EDX), Izod impact strength, conductivity, pencil hardness, and thermogravimetric characterizations of the nano composites were performed and the results will be presented.

Keywords: Gradient, Hybrid, Nanocomposite, Organic-Inorganic

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Authors: Leila Keshavarz Afshar, Hedieh Sajedi

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Estimation of biological brain age from MR images is a topic that has been much addressed in recent years due to the importance it attaches to early diagnosis of diseases such as Alzheimer's. In this paper, we use a 3D Convolutional Neural Network (CNN) to provide a method for estimating the biological age of the brain. The 3D-CNN model is trained by MRI data that has been normalized. In addition, to reduce computation while saving overall performance, some effectual slices are selected for age estimation. By this method, the biological age of individuals using selected normalized data was estimated with Mean Absolute Error (MAE) of 4.82 years.

Keywords: brain age estimation, biological age, 3D-CNN, deep learning, T1-weighted image, SPM, preprocessing, MRI, canny, gray matter

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Authors: Asmaa Zaki M., Ahmed Abd El Aziz, Heba A. Fayed, Moustafa H. Aly

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ISLs are the most popular choice for deep space communications because these links are attractive alternatives to present day microwave links. This paper explored the allowable high data rate in this link over different orbits, which is affected by variation in modulation scheme and detector type. Moreover, the objective of this paper is to optimize and analyze the performance of ISL in terms of Q-factor and Minimum Bit Error Rate (Min-BER) based on different detectors comprising some parameters.

Keywords: free space optics (FSO), field of view (FOV), inter satellite link (ISL), optical wireless communication (OWC)

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Authors: Priyankar P. Deka, Sutanu Samanta

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This paper describes the development of new class of epoxy based hybrid composites reinforced with jute and filled with rice husk flour. Rice husk flour is added in 0%, 1%, 3%, 5% by weight. Epoxy resin and triethylene tetramine (T.E.T.A) is used as matrix and hardener respectively. It investigates the mechanical properties of the composites and a comparison is done for monolithic jute composite and the filled ones. The specimens are prepared according to the ASTM standards and experimentation is carried out using INSTRON 8801. The result shows that with the increase of filler percentage the tensile properties increases but compressive and flexural properties decreases.

Keywords: jute, mechanical characterization, natural fiber, rice husk

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Authors: S. Bentata, W. Benstaali, A. Abbad, H. A. Bentounes, B. Bouadjemi

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The full potential linear augmented plane wave (FPLAPW) based on density-functional theory (DFT) is employed to study the electronic, magnetic and optical properties of some transition metals doped ZnSe. Calculations are carried out by varying the doped atoms. Four 3D transition elements were used as a dopant: Cr, Mn, Co and Cu in order to induce spin polarization. Our results show that, Mn and Cu-doped ZnSe could be used in spintronic devices only if additional dopants are introduced, on the contrary, transition elements showing delocalized quality such as Cr, and Co doped ZnSe might be promising candidates for application in spintronic.

Keywords: spin-up, spin-down, magnetic properties, transition metal, composite materials

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Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: Michel Moliere

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In the next decades, the thermal power generation segment will survive only if it achieves deep mutations, including drastical abatements of CO2 emissions and strong efficiency gains. In this challenging perspective, stationary gas turbines appear as serious candidates to lead the energy transition. Indeed, during the past decades, these turbomachines have made brisk technological advances in terms of efficiency, reliability, fuel flex (including the combustion of hydrogen), and the ability to hybridize with regenrables. It is, therefore, timely to summarize the progresses achieved by gas turbines in the recent past and to examine what are their assets to face the challenges of the energy transition.

Keywords: energy transition, gas turbines, decarbonization, power generation

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Authors: Mardiati Zain, Yetti Marlida, Elihasridas Elihasridas, Erpomen Erpomen, Andri Andri

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Background: Livestock productivity is greatly influenced by the energy and protein balance in diet. This study aimed to determine the energy and protein balance of male Simenthal cattle diet with protein and energy levels. The experimental design used was a randomized block design (RBD) 2x3x3 factorial design. There are two factors namely A level of energy diet that is 65% and 70% TDN. Factor B is a protein level of diet used were 10, 12 and 14% and each treatment is repeated three times. The weight of Simenthal cattle used ranged between 240 - 300 kg. Diet consisted of ammoniated rice straw and concentrated with ratio 40:60. Concentrate consisted of palm kernel cake, rice brain, cassava, mineral, and urea. The variables measured were digestibility of dry matter, organic matter and fiber, dry matter intake, daily gain, feed efficiency and blood characteristic. Results: There was no interaction between protein and energy level of diet on the nutrients intake (DM intake, OM intake, CP intake), weight gain and efficiency (P < 0.01). There was an interaction between protein and energy level of diet on digestibility (DM, OM, CP and allantoin urine (P > 0.01) Nutrients intake decreases with increasing levels of energy and protein diet, while nutrient digestibility, Avarage daily gain and feed efficiency increases with increasing levels of energy and protein diet. Conclusions: The result can be concluded that the best treatment was A2B1 which is energy level 70% TDN and protein 10%, where are dry matter intake 7.66 kg/d, daily gain 1.25 kg/d, feed efficiency 16.12%, and dry matter and organic matter digestibility 64.08 and 69.42% respectively.

Keywords: energy and protein ratio, simenthal cattle, rice straw ammoniated, digestibility

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Authors: H. Unal, A. Mimaroglu, I. Ozsoy

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In this study, the mechanical properties of micro filled epoxy composites were investigated. The matrix material is epoxy. Micro fillers are Al2O3 and TiO2 added in 10-30 wt% by weight ratio. Test samples were prepared using an open mould type die. Tensile, three point bending and hardness tests were carried out. The tensile strength, elastic modulus, elongation at break, flexural strength, flexural modulus and the hardness of the composite materials were obtained and evaluated. It was seen from the results that the level of the mechanical properties of the epoxy composites is highly influenced by micro filler content.

Keywords: composites, epoxy, fillers, mechanical properties

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Authors: Dumont Maxime, Correia Carlos, Sauvage Jean-François, Schwartz Noah, Gray Morgan

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Context: The concept of the segmented telescope is unavoidable to build extremely large telescopes (ELT) in the quest for spatial resolution, but it also allows one to fit a large telescope within a reduced volume of space (JWST) or into an even smaller volume (Standard Cubesat). Cubesats have tight constraints on the computational burden available and the small payload volume allowed. At the same time, they undergo thermal gradients leading to large and evolving optical aberrations. The pupil segmentation comes nevertheless with an obvious difficulty: to co-phase the different segments. The CubeSat constraints prevent the use of a dedicated wavefront sensor (WFS), making the focal-plane images acquired by the science detector the most practical alternative. Yet, one of the challenges for the wavefront sensing is the non-linearity between the image intensity and the phase aberrations. Plus, for Earth observation, the object is unknown and unrepeatable. Recently, several studies have suggested Neural Networks (NN) for wavefront sensing; especially convolutional NN, which are well known for being non-linear and image-friendly problem solvers. Aims: We study in this paper the prospect of using NN to measure the phasing aberrations of a segmented pupil from the focal-plane image directly without a dedicated wavefront sensing. Methods: In our application, we take the case of a deployable telescope fitting in a CubeSat for Earth observations which triples the aperture size (compared to the 10cm CubeSat standard) and therefore triples the angular resolution capacity. In order to reach the diffraction-limited regime in the visible wavelength, typically, a wavefront error below lambda/50 is required. The telescope focal-plane detector, used for imaging, will be used as a wavefront-sensor. In this work, we study a point source, i.e. the Point Spread Function [PSF] of the optical system as an input of a VGG-net neural network, an architecture designed for image regression/classification. Results: This approach shows some promising results (about 2nm RMS, which is sub lambda/50 of residual WFE with 40-100nm RMS of input WFE) using a relatively fast computational time less than 30 ms which translates a small computation burder. These results allow one further study for higher aberrations and noise.

Keywords: wavefront sensing, deep learning, deployable telescope, space telescope

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Authors: Nur Suraya Anis Ahmad Bakhtiar, Hazizan Md Akil

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In the present work, the dielectric properties of Epoxy/MWCNTs-muscovite HYBRID and MIXED composites based on ratio 30:70 were studies. The multi-wall carbon nanotubes (MWCNTs) were prepared by two method; (a) muscovite-MWCNTs hybrids were synthesized by chemical vapor deposition (CVD) and (b) physically mixing of muscovite with MWCNTs. The effect of different preparations of the composites and filler loading was evaluated. It is revealed that the dielectric constants of HYBRID epoxy composites are slightly higher compared to MIXED epoxy composites. It is also indicated that the dielectric constant increased by increases the MWCNTs filler loading.

Keywords: muscovite, epoxy, dielectric properties, hybrid composite

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Authors: Santhana Krishnan R, Preetha C

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Sandwich construction with strong and stiffness facing and light weight cores is increasingly cores being used in structures where the predominant loads are flexural. The objective of this study is to improve the flexural performances of foam core sandwich composite via structural core modifications considering the ease of application. The performances of single core perforated and divided core perforated sandwich composites are compared with each other. The future demands of sandwich composites in recent years on aeronautics and marine industries are being increasing in their research needs and these materials has their superior properties for upgrading engineering products.

Keywords: sandwich composites, perforated cores, flexural test, single and divided core perforated

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Authors: O. Lopez, F. Pedro, A. Tadeu, J. Antonio, A. Coelho

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The future of the railway industry lies in the innovation of lighter, more efficient and more sustainable trains. Weight optimizations in railway vehicles allow reducing power consumption and CO₂ emissions, increasing the efficiency of the engines and the maximum speed reached. Additionally, they reduce wear of wheels and rails, increase the space available for passengers, etc. Among the various systems that integrate railway interiors, the flooring system is one which has greater impact both on passenger safety and comfort, as well as on the weight of the interior systems. Due to the high weight saving potential, relative high mechanical resistance, good acoustic and thermal performance, ease of modular design, cost-effectiveness and long life, the use of new sustainable composite materials and panels provide the latest innovations for competitive solutions in the development of flooring systems. However, one of the main drawbacks of the flooring systems is their relatively poor resistance to point loads. Point loads in railway interiors can be caused by passengers or by components fixed to the flooring system, such as seats and restraint systems, handrails, etc. In this way, they can originate higher fatigue solicitations under service loads or zones with high stress concentrations under exceptional loads (higher longitudinal, transverse and vertical accelerations), thus reducing its useful life. Therefore, to verify all the mechanical and functional requirements of the flooring systems, many physical prototypes would be created during the design phase, with all of the high costs associated with it. Nowadays, the use of virtual prototyping methods by computer-aided design (CAD) and computer-aided engineering (CAE) softwares allow validating a product before committing to making physical test prototypes. The scope of this work was to current computer tools and integrate the processes of innovation, development, and manufacturing to reduce the time from design to finished product and optimise the development of the product for higher levels of performance and reliability. In this case, the mechanical response of several sandwich panels with different cores, polystyrene foams, and composite corks, were assessed, to optimise the weight and the mechanical performance of a flooring solution for railways. Sandwich panels with aluminum face sheets were tested to characterise its mechanical performance and determine the polystyrene foam and cork properties when used as inner cores. Then, a railway flooring solution was fully modelled (including the elastomer pads to provide the required vibration isolation from the car body) and perform structural simulations using FEM analysis to comply all the technical product specifications for the supply of a flooring system. Zones with high stress concentrations are studied and tested. The influence of vibration modes on the comfort level and stability is discussed. The information obtained with the computer tools was then completed with several mechanical tests performed on some solutions, and on specific components. The results of the numerical simulations and experimental campaign carried out are presented in this paper. This research work was performed as part of the POCI-01-0247-FEDER-003474 (coMMUTe) Project funded by Portugal 2020 through COMPETE 2020.

Keywords: cork agglomerate core, mechanical performance, numerical simulation, railway flooring system

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Authors: Jose Gois

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The paper presents the development of a porous porcelain frappe with thermochromic visualization for port wines, having as a partner the Institute of Vinhos do Douro and Porto. This ceramic frappe is intended to promote the cooling and maintenance of the temperature of port wines through porous ceramic materials, consisting of a porcelain composite with sawdust addition, so as to contain, on the one hand, the similar cooling properties of the terracotta and, on the other, the resistance of materials such as porcelain. The application of the thermochromic element makes it possible to see if the wine is at optimal service temperatures, allowing users to drink the wine in the ideal conditions and contributing to more efficient maintenance of the service.

Keywords: design, frappe, porcelain, porous, thermochromic

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Authors: Naeem Ullah, Menglan Duan, Mac Darlington Uche Onuoha

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The lowering of subsea equipment into the deep waters is a challenging job due to the harsh offshore environment. Many researchers have introduced various installation systems to deploy the payload safely into the deep oceans. In general practice, dual floating vessels are not employed owing to the prevalent safety risks and hazards caused by ever-increasing dynamical effects sourced by mutual interaction between the bodies. However, while keeping in the view of the optimal grounds, such as economical one, the Y-method, the two conventional tugboats supporting the equipment by the two independent strands connected to a tri-plate above the equipment, has been employed to study multibody dynamics of the dual barge lifting operations. In this study, the two tugboats and the suspended payload (Y-method) are deployed for the lowering of subsea equipment into the deep waters as a multibody dynamic system. The two-wire ropes are used for the lifting and installation operation by this Y-method installation system. 6-dof (degree of freedom) for each body are considered to establish coupled 18-dof multibody model by embedding technique or velocity transformation technique. The fundamental and prompt advantage of this technique is that the constraint forces can be eliminated directly, and no extra computational effort is required for the elimination of the constraint forces. The inertial frame of reference is taken at the surface of the water as the time-independent frame of reference, and the floating frames of reference are introduced in each body as the time-dependent frames of reference in order to formulate the velocity transformation matrix. The local transformation of the generalized coordinates to the inertial frame of reference is executed by applying the Euler Angle approach. The spherical joints are articulated amongst the multibody as the kinematic joints. The hydrodynamic force, the two-strand forces, the hydrostatic force, and the mooring forces are taken into consideration as the external forces. The radiation force of the hydrodynamic force is obtained by employing the Cummins equation. The wave exciting part of the hydrodynamic force is obtained by using force response amplitude operators (RAOs) that are obtained by the commercial solver ‘OpenFOAM’. The strand force is obtained by considering the wire rope as an elastic spring. The nonlinear hydrostatic force is obtained by the pressure integration technique at each time step of the wave movement. The mooring forces are evaluated by using Faltinsen analytical approach. ‘The Runge Kutta Method’ of Fourth-Order is employed to evaluate the coupled equations of motion obtained for 18-dof multibody model. The results are correlated with the simulated Orcaflex Model. Moreover, the results from Orcaflex Model are compared with the MOSES Model from previous studies. The MBDS of single barge lifting operation from the former studies are compared with the MBDS of the established dual barge lifting operation. The dynamics of the dual barge lifting operation are found larger in magnitude as compared to the single barge lifting operation. It is noticed that the traction at the top connection point of the cable decreases with the increase in the length, and it becomes almost constant after passing through the splash zone.

Keywords: dual barge lifting operation, Y-method, multibody dynamics, shipbuilding, installation of subsea equipment, shipbuilding

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Authors: Abir Abdessalem, Sahbi Tamboura, J. Fitoussi, Hachmi Ben Daly, Abbas Tcharkhtchi

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Dynamic mechanical analysis (DMA) is one of the most used experimental techniques to investigate the temperature and frequency dependence of the mechanical behavior of viscoelastic materials. The measured data are generally shifted by the application of the principle of the time– temperature superposition (TTS) to obtain the viscoelastic system’s master curve. The aim of this work is to show the methodology to define the horizontal shift factor to be applied to the storage modulus measured in order to indicate the validity of (TTS) principle for this material system. This principle was successfully used to determine the long-term properties of the Sheet Moulding Compound (SMC) composites.

Keywords: composite material, dynamic mechanical analysis, SMC composites, viscoelastic behavior, modeling

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Authors: Isam A. H. Al Zubaidy

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A quick process may be needed to get the benefit the big generated quantity of waste oil sludge (WOS). The process includes the mixing process of WOS with commercial diesel fuel. Different ratios of WOS to diesel fuel were prepared ranging 1:1 to 20:1 by mass. The mixture was continuously mixing for 10 minutes using bench type overhead stirrer and followed by filtration process to separate the soil waste from filtrate oil product. The quantity and the physical properties of the oil filtrate were measured. It was found that the addition of up to 15% WOS to diesel fuel was accepted without dramatic changes to the properties of diesel fuel. The amount of waste oil sludge was decreased by about 60% by mass. This means that about 60 % of the mass of sludge was recovered as light fuel oil. The physical properties of the resulting fuel from 10% sludge mixing ratio showed that the specific gravity, ash content, carbon residue, asphaltene content, viscosity, diesel index, cetane number, and calorific value were affected slightly. The color was changed to light black color. The sulfur content was increased also. This requires other processes to reduce the sulfur content of the resulting light fuel. A new desulfurization process was achieved using adsorption techniques with activated biomaterial to reduce the sulfur content to acceptable limits. Adsorption process by ZnCl₂ activated date palm kernel powder was effective for improvement of the physical properties of diesel like fuel. The final sulfur content was increased to 0.185 wt%. This diesel like fuel can be used in all tractors, buses, tracks inside and outside the refineries. The solid remaining seems to be smooth and can be mixed with asphalt mixture for asphalting the roads or can be used with other materials as an asphalt coating material for constructed buildings. Through this process, valuable fuel has been recovered, and the amount of waste material had decreased.

Keywords: oil sludge, diesel fuel, blending process, filtration process

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Authors: Luisa Mesquita Oliveira Ribeiro, Alexei Manso Correa Machado

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Handwritten signature is a unique form for recognizing an individual, used to discern documents, carry out investigations in the criminal, legal, banking areas and other applications. Signature verification is based on large amounts of biometric data, as they are simple and easy to acquire, among other characteristics. Given this scenario, signature forgery is a worldwide recurring problem and fast and precise techniques are needed to prevent crimes of this nature from occurring. This article carried out a study on the efficiency of the Capsule Network in analyzing and recognizing signatures. The chosen architecture achieved an accuracy of 98.11% and 80.15% for the CEDAR and GPDS databases, respectively.

Keywords: biometrics, deep learning, handwriting, signature forgery

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Authors: Jason Michael Crozier

Abstract:

The wrestling territories of the mid-twentieth century in the United States are widely considered the birthplace of modern professional wrestling, and by many professional wrestlers, to be a beacon of hope for the easing of racial tensions during the civil rights era and beyond. The performers writing on this period speak of racial equality but fail to acknowledge the exploitation of black athletes as a racialized capital commodity who suffered the challenges of systemic racism, codified by a false narrative of aspirational exceptionalism and equality measured by audience diversity. The promoters’ ability to equate racial and capital exploitation with equality leads to a broader discussion of the history of Muscular Christianity in the United States and the exploitation of black bodies. Narratives of racial erasure that dominate the historical discourse when examining athleticism and exceptionalism redefined how blackness existed and how physicality and race are conceived of in sport and entertainment spaces. When discussing the implications of race and professional wrestling, it is important to examine the role of promotions as ‘imagined communities’ where the social agency of wrestlers is defined and quantified based on their ‘desired elements’ as a performer. The intentionally vague nature of this language masks a deep history of racialization that has been perpetuated by promoters and never fully examined by scholars. Sympathetic racism and the omission of cultural identity are also key factors in the limitations and racial barriers placed upon black athletes in the squared circle. The use of sympathetic racism within professional wrestling during the twentieth century defined black athletes into two distinct categorizations, the ‘black savage’ or the ‘black minstrel’. Black wrestlers of the twentieth century were defined by their strength as a capital commodity and their physicality rather than their knowledge of the business and in-ring skill. These performers had little agency in their ability to shape their own character development inside and outside the ring. Promoters would often create personas that heavily racialized the performer by tying them to a regional past or memory, such as that of slavery in the deep south using dog collar matches and adoring black characters in chains. Promoters softened cultural memory by satirizing the historic legacy of slavery and the black identity.

Keywords: sympathetic racism, social agency, racial commodification, stereotyping

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Authors: N. Burtebayev, Sh. Hamada, Zh. Kerimkulov, D. K. Alimov, A. V. Yushkov, N. Amangeldi, A. N. Bakhtibaev

Abstract:

The main aim of the current work is to examine if 14N is candidate to be clusterized nuclei or not. In order to check this attendance, we have measured the angular distributions for 14N ion beam elastically scattered on 12C target nuclei at different low energies; 17.5, 21, and 24.5MeV which are close to the Coulomb barrier energy for 14N+12C nuclear system. Study of various transfer reactions could provide us with useful information about the attendance of nuclei to be in a composite form (core + valence). The experimental data were analyzed using two approaches; Phenomenological (Optical Potential) and semi-microscopic (Double Folding Potential). The agreement between the experimental data and the theoretical predictions is fairly good in the whole angular range.

Keywords: deuteron transfer, elastic scattering, optical model, double folding, density distribution

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Authors: D. Signore, M. Ferraiuolo, P. Caramuta, O. Petrella, C. Toscano

Abstract:

The Digital Image Correlation (DIC) is a newly developed optical technique that is spreading in all engineering sectors because it allows the non-destructive estimation of the entire surface deformation without any contact with the component under analysis. These characteristics make the DIC very appealing in all the cases the global deformation state is to be known without using strain gages, which are the most used measuring device. The DIC is applicable to any material subjected to distortion caused by either thermal or mechanical load, allowing to obtain high-definition mapping of displacements and deformations. That is why in the civil and the transportation industry, DIC is very useful for studying the behavior of metallic materials as well as of composite materials. DIC is also used in the medical field for the characterization of the local strain field of the vascular tissues surface subjected to uniaxial tensile loading. DIC can be carried out in the two dimension mode (2D DIC) if a single camera is used or in a three dimension mode (3D DIC) if two cameras are involved. Each point of the test surface framed by the cameras can be associated with a specific pixel of the image, and the coordinates of each point are calculated knowing the relative distance between the two cameras together with their orientation. In both arrangements, when a component is subjected to a load, several images related to different deformation states can be are acquired through the cameras. A specific software analyzes the images via the mutual correlation between the reference image (obtained without any applied load) and those acquired during the deformation giving the relative displacements. In this paper, a metrological characterization of the digital image correlation is performed on aluminum and composite targets both in static and dynamic loading conditions by comparison between DIC and strain gauges measures. In the static test, interesting results have been obtained thanks to an excellent agreement between the two measuring techniques. In addition, the deformation detected by the DIC is compliant with the result of a FEM simulation. In the dynamic test, the DIC was able to follow with a good accuracy the periodic deformation of the specimen giving results coherent with the ones given by FEM simulation. In both situations, it was seen that the DIC measurement accuracy depends on several parameters such as the optical focusing, the parameters chosen to perform the mutual correlation between the images and, finally, the reference points on image to be analyzed. In the future, the influence of these parameters will be studied, and a method to increase the accuracy of the measurements will be developed in accordance with the requirements of the industries especially of the aerospace one.

Keywords: accuracy, deformation, image correlation, mechanical analysis

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Authors: R. S. Vikaash, S. Vinodh, T. S. Sai Prashanth

Abstract:

Six sigma is a defect reduction strategy enabling modern organizations to achieve business prosperity. The practitioners are in need to select best six sigma project among the available alternatives to achieve customer satisfaction. In this circumstance, this article presents a study in which six sigma project selection is formulated as Multi-Criteria Decision-Making(MCDM) problem and the best project has been found using AHP. Five main governing criteria and 14 sub criteria are being formulated. The decision maker’s inputs were gathered and computations were performed. The project with the high values from the set of projects is selected as the best project. Based on calculations, Project “P1”is found to be the best and further deployment actions have been undertaken in the organization.

Keywords: six Sigma, project selection, MCDM, analytic hierarchy process, business prosperity

Procedia PDF Downloads 333

Authors: Jana Petrů, Tomáš Zlámal, Robert Čep, Lenka Čepová

Abstract:

This article is focused on the thermal spray coating machining issue. Those are irreplaceable in many areas of nowadays industrial branches such as aerospace industry, mostly thanks to their excellent qualities in production and also in renovation of machinery parts. The principals of thermal spraying and elementary diversification are described in introduction. Plasma coating method of composite materials -cermets- is described more thoroughly. The second part describes thermal spray coating machining and grinding in detail. This part contains suggestion of appropriate grinding tool and assessment of cutting conditions used for grinding a given part. Conclusion describes a problem which occurred while grinding a cermet thermal spray coating with a specially designed grindstone and a way to solve this problem.

Keywords: coating, aerospace, plasma, grinding

Procedia PDF Downloads 544