Search results for: deep plate loading test

Authors: Navpreet Kaur, Randhir Singh

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Diabetic neuropathy is one of the most common microvascular complications of diabetes mellitus which affects more than 50% of diabetic patients. The present study targeted oxidative stress mediated nerve damage in diabetic rats using a hydro-alcohol extract of Cucurbita pepo L. (Family: Cucurbitaceae) and its potential in treatment of diabetic neuropathy. Diabetes neuropathy was induced in Wistar rats by injection of streptozotocin (65 mg/kg, i.p.) 15 min after Nicotinamide (230 mg/kg, i.p.) administration. Hydro-alcohol extract of C. pepo seeds was assessed by oral administration at 100, 200 and 400 mg/kg in STZ-nicotinamide induced diabetic rats. Thermal hyperalgesia (Eddy's hot plate and tail immersion), mechanical hyperalgesia (Randall-Selitto) and tactile allodynia (Von Frey hair tests) were evaluated in all groups of streptozotocin diabetic rats to assess the extent of neuropathy. Tissue (sciatic nerve) antioxidant enzymes (SOD, CAT, GSH and LPO) levels were measured along with the formation of AGEs in serum to assess the effect of hydro-alcohol extract of C. pepo in ameliorating oxidative stress. Diabetic rats exhibited significantly decreased tail-flick latency in the tail-immersion test and decreased paw withdrawal threshold in both Randall-Selitto and von-Frey hair test. A decrease in the nociceptive threshold was accompanied by significantly increased oxidative stress in sciatic nerve of diabetic rats. Treatment with the C. pepo hydro-alcohol extract significantly attenuated all the behavioral and biochemical alterations in a dose-dependent manner. C. pepo attenuated the diabetic condition and also reversed neuropathic pain through modulation of oxidative stress and thus it may find application as a possible therapeutic agent against diabetic neuropathy.

Keywords: advanced glycation end products, antioxidant enzymes, cucurbita pepo, hyperglycemia

Procedia PDF Downloads 301

Authors: Prathiksha Kamath, Pratibha Jamkhandi, Prateek Ghanti, Priyanshu Gupta, M. Lakshmi Neelima

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Combining Image Captioning and Visual Question Answering (VQA) tasks have emerged as a new and exciting research area. The image captioning task involves generating a textual description that summarizes the content of the image. VQA aims to answer a natural language question about the image. Both these tasks include computer vision and natural language processing (NLP) and require a deep understanding of the content of the image and semantic relationship within the image and the ability to generate a response in natural language. There has been remarkable growth in both these tasks with rapid advancement in deep learning. In this paper, we present a comprehensive review of recent progress in combining image captioning and visual question-answering (VQA) tasks. We first discuss both image captioning and VQA tasks individually and then the various ways in which both these tasks can be integrated. We also analyze the challenges associated with these tasks and ways to overcome them. We finally discuss the various datasets and evaluation metrics used in these tasks. This paper concludes with the need for generating captions based on the context and captions that are able to answer the most likely asked questions about the image so as to aid the VQA task. Overall, this review highlights the significant progress made in combining image captioning and VQA, as well as the ongoing challenges and opportunities for further research in this exciting and rapidly evolving field, which has the potential to improve the performance of real-world applications such as autonomous vehicles, robotics, and image search.

Keywords: image captioning, visual question answering, deep learning, natural language processing

Procedia PDF Downloads 78

Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

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The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

Procedia PDF Downloads 123

Authors: S. Daqiqeh Rezaei, S. Mohajerzadeh, M. R. Sharifi

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Pedicle screws are used to stabilize vertebrae and treat several types of spinal diseases and injuries. Multiaxial pedicle screws are a type of pedicle screw that increase surgical versatility, but they also increase design complexity. Failure of multiaxial pedicle screws caused by static loading, dynamic loading and fatigue can lead to irreparable damage to the patient. Inappropriate deformation of the multiaxial pedicle screw tulip can cause system failure. Investigation of deformation and stress in these tulips can be employed to optimize multiaxial pedicle screw design. The sensitivity of this matter necessitates precise analyzing and modeling of pedicle screws. In this work, three commercial multiaxial pedicle screw tulips and a newly designed tulip are investigated using finite element analysis. Employing video measuring machine (VMM), tulips are modeled. Afterwards, utilizing ANSYS, static analysis is performed on these models. In the end, stresses and displacements of the models are compared.

Keywords: pedicle screw, multiaxial pedicle screw, finite element analysis, static analysis

Procedia PDF Downloads 375

Authors: Bernd Engel, Sara Salman Hassan Al-Maeeni

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A substantial amount of natural resources are nowadays consumed at a growing rate, as humans all over the world used materials obtained from the Earth. Machinery manufacturing industry is one of the major resource consumers on a global scale. Even though the incessant finding out of the new material, metals, and resources, it is urgent for the industry to develop methods to use the Earth's resources intelligently and more sustainable than before. Re-engineering of machine tools regarding design and failure analysis is an approach whereby out-of-date machines are upgraded and returned to useful life. To ensure the reliable future performance of the used machine components, it is essential to investigate the machine component failure through the material, design, and surface examinations. This paper presents an experimental approach aimed at inspecting the shaft of the rotary draw bending machine as a case to study. The testing methodology, which is based on the principle of the three-point bending test, allows assessing the shaft elastic behavior under loading. Furthermore, the shaft elastic characteristics include the maximum linear deflection, and maximum bending stress was determined by using an analytical approach and finite element (FE) analysis approach. In the end, the results were compared with the ones obtained by the experimental approach. In conclusion, it is seen that the measured bending deflection and bending stress were well close to the permissible design value. Therefore, the shaft can work in the second life cycle. However, based on previous surface tests conducted, the shaft needs surface treatments include re-carburizing and refining processes to ensure the reliable surface performance.

Keywords: deflection, FE analysis, shaft, stress, three-point bending

Procedia PDF Downloads 163

Authors: Mst Shapna Akter, Hossain Shahriar

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One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a largescale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of opensource functions that point to potential exploits. We developed an efficient and scalable vulnerability detection method based on deep neural network models that learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the dependency. Moreover, we keep the semantic and syntactic information using state-of-the-art word embedding algorithms such as glove and fastText. The embedded vectors are subsequently fed into deep learning networks such as LSTM, BilSTM, LSTM-Autoencoder, word2vec, BERT, and GPT-2 to classify the possible vulnerabilities. Furthermore, we proposed a neural network model which can overcome issues associated with traditional neural networks. Evaluation metrics such as f1 score, precision, recall, accuracy, and total execution time have been used to measure the performance. We made a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. We found that all of the deep learning models provide comparatively higher accuracy when we use semantic and syntactic information as the features but require higher execution time as the word embedding the algorithm puts on a bit of complexity to the overall system.

Keywords: cyber security, vulnerability detection, neural networks, feature extraction

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Authors: Sonia David, Uma Warrier

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Background: Film therapy is the use of commercial or non-commercial films to enhance healing for therapeutic purposes. Objectives: The mixed-method study aims to evaluate the effect of film-based counseling on body image dissatisfaction among adolescents to precisely ascertain the cause of the alteration in body image dissatisfaction due to the said intervention. Method: The one group pre-test post-test research design study using inferential statistics and thematic analysis is based on a pre-test post-test design conducted on 44 school-going adolescents between 13 and 17. The Body Shape Questionnaire (BSQ- 34) was used as a pre-test and post-test measure. The film-based counseling intervention model was used through individual counseling sessions. The analysis involved paired sample t-test used to examine the data quantitatively, and thematic analysis was used to evaluate qualitative data. Findings: The results indicated that there is a significant difference between the pre-test and post-test means. Since t(44)= 9.042 is significant at a 99% confidence level, it is ascertained that film-based counseling intervention reduces body image dissatisfaction. The five distinct themes from the thematic analysis are “acceptance, awareness, empowered to change, empathy, and reflective.” Novelty: The paper originally contributes to the repertoire of research on film therapy as a successful counseling intervention for addressing the challenges of body image dissatisfaction. This study also opens avenues for considering alteration of teaching pedagogy to include video-based learning in various subjects.

Keywords: body image dissatisfaction, adolescents, film-based counselling, film therapy, acceptance and commitment therapy

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Authors: Diego Aguirre, Olac Fuentes

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In this paper, we present a taxonomy of weight initialization schemes used in deep learning. We survey the most representative techniques in each class and compare them in terms of overhead cost, convergence rate, and applicability. We also introduce a new weight initialization scheme. In this technique, we perform an initial feedforward pass through the network using an initialization mini-batch. Using statistics obtained from this pass, we initialize the weights of the network, so the following properties are met: 1) weight matrices are orthogonal; 2) ReLU layers produce a predetermined number of non-zero activations; 3) the output produced by each internal layer has a unit variance; 4) weights in the last layer are chosen to minimize the error in the initial mini-batch. We evaluate our method on three popular architectures, and a faster converge rates are achieved on the MNIST, CIFAR-10/100, and ImageNet datasets when compared to state-of-the-art initialization techniques.

Keywords: deep learning, image classification, supervised learning, weight initialization

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Authors: Joseph Fitoussi, Mohammadali Shirinbayan, Abbas Tcharkhtchi

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Due to material flow during processing, short fiber reinforced composites structures obtained by injection or compression molding generally present strong spatial microstructure variation. On the other hand, quasi-static, dynamic, and fatigue behavior of these materials are highly dependent on microstructure parameters such as fiber orientation distribution. Indeed, because of complex damage mechanisms, SFRC structures design is a key challenge for safety and reliability. In this paper, we propose a micromechanical model allowing prediction of damage behavior of real structures as a function of microstructure spatial distribution. To this aim, a statistical damage criterion including strain rate and fatigue effect at the local scale is introduced into a Mori and Tanaka model. A critical local damage state is identified, allowing fatigue life prediction. Moreover, the multi-scale model is coupled with an experimental intrinsic link between damage under monotonic loading and fatigue life in order to build an abacus giving Tsai-Wu failure criterion parameters as a function of microstructure and targeted fatigue life. On the other hand, the micromechanical damage model gives access to the evolution of the anisotropic stiffness tensor of SFRC submitted to complex thermomechanical loading, including quasi-static, dynamic, and cyclic loading with temperature and amplitude variations. Then, the latter is used to fill out microstructure dependent material cards in finite element analysis for design optimization in the case of complex loading history. The proposed methodology is illustrated in the case of a real automotive component made of sheet molding compound (PSA 3008 tailgate). The obtained results emphasize how the proposed micromechanical methodology opens a new path for the automotive industry to lighten vehicle bodies and thereby save energy and reduce gas emission.

Keywords: short fiber reinforced composite, structural design, damage, micromechanical modelling, fatigue, strain rate effect

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Authors: Androniki-Anna Doulgeroglou, Panagiotis Kotronis, Giulio Sciarra, Catherine Bouillon

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The interaction diagrams are functions that define ultimate states expressed in terms of generalized forces (axial force, bending moment and shear force). Two characteristic states for reinforced concrete (RC) sections are proposed: the first characteristic state corresponds to the yield of the reinforcement bars and the second to the peak values of the generalized forces generalized displacements curves. 3D numerical simulations are then conducted for RC columns and the global responses are compared to experimental results. Interaction diagrams for combined flexion, shear and axial force loading conditions are numerically produced for symmetrically RC square sections for different reinforcement ratios. Analytical expressions of the interaction diagrams are also proposed, satisfying the condition of convexity. Comparison with interaction diagrams from the Eurocode is finally presented for the study cases.

Keywords: analytical convex expressions, finite element method, interaction diagrams, reinforced concrete

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Authors: Mohammadjavad Yaghoubi, Arul Arulrajah, Mahdi M. Disfani, Suksun Horpibulsuk, Myint W. Bo, Stephen P. Darmawan

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Utilising waste materials, such as fly ash (FA) and slag (S) stockpiled in landfills, has drawn the attention of researchers and engineers in the recent years. There is a great potential for usage of these wastes in ground improvement projects, especially where deep deposits of soft compressible soils exist. This paper investigates the changes in the strength development of a high water content soft soil stabilised with alkaline activated FA and S, termed as geopolymer binder, to use in deep soil mixing technology. The strength improvement and the changes in the microstructure of the mixtures have been studied. The results show that using FA and S-based geopolymers can increases the strength significantly. Furthermore, utilising FA and S in ground improvement projects, where large amounts of binders are required, can be a solution to the disposal of these wastes.

Keywords: alkaline activation, fly ash, geopolymer, slag, strength development

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Authors: A. Hamma, A. Pegoretti

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The paper focuses on the evaluation of mechanical performances and viscoelastic behaviour of starch-grafted-PP reinforced with kenaf fibres. Investigations were carried out on composites prepared by melt compounding and compression molding. Two aspects have been taken into account, the effects of various fibres loading rates (10, 20 and 30 wt.%) and the fibres aspect ratios (L/D=30 and 160). Good fibres/matrix interaction has been evidenced by SEM observations. However, processing induced variation of fibre length quantified by optical microscopy observations. Tensile modulus and ultimate properties, hardness and tensile impact stress, were found to remarkably increase with fibre loading. Moreover, short term tensile creep tests have proven that kenaf fibres improved considerably the creep stability. Modelling of creep behaviour by a four parameter Burger model was successfully used. An empirical equation involving Halpin-Tsai semi empirical model was also used to predict the elastic modulus of composites.

Keywords: mechanical properties, creep, fibres, thermoplastic composites, starch-grafted-PP

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Authors: M. H. Aissa, Amar Bouzid Dj

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As known, many countries are now planning to build new wind farms with high capacity up to 5MW. Consequently, the size of the foundation increase. These kinds of structures are subject to fatigue damage from environmental loading mainly due to wind and waves as well as from cyclic loading imposed through the rotational frequency (1P) through mass and aerodynamic imbalances and from the blade passing frequency (3P) of the wind turbine which make them behavior dynamically very sensitive. That is why natural frequency must be determined with accuracy from the existing data of the soil and the foundation stiffness sources of uncertainties, to avoid the resonance of the system. This paper presents analytical expressions of stiffness foundation with large diameter in linear soil behavior in different soil stiffness profile. To check the accuracy of the proposed formulas, a mathematical model approach based on non-dimensional parameters is used to calculate the natural frequency taking into account the soil structure interaction (SSI) compared with the p-y method and measured frequency in the North Sea Wind farms.

Keywords: offshore wind turbines, semi analytical FE analysis, p-y curves, piles foundations

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Authors: Christos Theoharatos, Dimitris Tsourounis, Spiros Oikonomou, Andreas Makedonas

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This paper focuses on the problem of visually inspecting and recognizing the road conditions in front of moving vehicles, targeting automotive scenarios. The goal of road inspection is to identify whether the road is slippery or not, as well as to detect possible anomalies on the road surface like potholes or body bumps/humps. Our work is based on an artificial intelligence methodology for real-time monitoring of road conditions in autonomous driving scenarios, using state-of-the-art deep convolutional neural network (CNN) techniques. Initially, the road and ego lane are segmented within the field of view of the camera that is integrated into the front part of the vehicle. A novel classification CNN is utilized to identify among plain and slippery road textures (e.g., wet, snow, etc.). Simultaneously, a robust detection CNN identifies severe surface anomalies within the ego lane, such as potholes and speed bumps/humps, within a distance of 5 to 25 meters. The overall methodology is illustrated under the scope of an integrated application (or system), which can be integrated into complete Advanced Driver-Assistance Systems (ADAS) systems that provide a full range of functionalities. The outcome of the proposed techniques present state-of-the-art detection and classification results and real-time performance running on AI accelerator devices like Intel’s Myriad 2/X Vision Processing Unit (VPU).

Keywords: deep learning, convolutional neural networks, road condition classification, embedded systems

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Authors: Cathal Merz, Gareth O’Donnell

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Coil reinforced thin-walled (CRTW) tubes are used in medicine to treat problems affecting blood vessels within the body through minimally invasive procedures. The CRTW tube considered in this research makes up part of such a device and is inserted into the patient via their femoral or brachial arteries and manually navigated to the site in need of treatment. This procedure replaces the requirement to perform open surgery but is limited by reduction of blood vessel lumen diameter and increase in tortuosity of blood vessels deep in the brain. In order to maximize the capability of these procedures, CRTW tube devices are being manufactured with decreasing wall thicknesses in order to deliver treatment deeper into the body and to allow passage of other devices through its inner diameter. This introduces significant stresses to the device materials which have resulted in an observed increase in the breaking of the proximal segment of the device into two separate pieces after it has failed by buckling. As there is currently no international standard for measuring the mechanical properties of these CRTW tube devices, it is difficult to accurately analyze this problem. The aim of the current work is to address this discrepancy in the biomedical device industry by developing a measurement system that can be used to quantify the effect of process and design changes on CRTW tube performance, aiding in the development of better performing, next generation devices. Using materials testing frames, micro-computed tomography (micro-CT) imaging, experiment planning, analysis of variance (ANOVA), T-tests and regression analysis, test methods have been developed for assessing the impact of process and design changes on the device. The major findings of this study have been an insight into the suitability of buckle and three-point bend tests for the measurement of the effect of varying processing factors on the device’s performance, and guidelines for interpreting the output data from the test methods. The findings of this study are of significant interest with respect to verifying and validating key process and design changes associated with the device structure and material condition. Test method integrity evaluation is explored throughout.

Keywords: neurovascular catheter, coil reinforced tube, buckling, three-point bend, tensile

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Authors: Elizabeth Loza-Valerdi, Victor Pardiñas-Rios, Arnulfo Pluma-Pluma, Andres Breton-Toral, Julio Cercado-Jaramillo

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The purification processes for mixtures of isomeric monosaccharides using industrial chromatographic methods poses a serious technical challenge. Mixtures of 2 or 3 monosaccharides are difficult to separate by strictly physical or chemical techniques. Differential fermentation by microbial cultures is an increasingly interesting way of selective enrichment in a particular kind of monosaccharides when a mixture of them is present in the solution, and only one has economical value. Osmotolerant yeast cultures provide an interesting source of biocatalysts for the selective catabolism of monosaccharides in media containing high concentrations of total soluble sugars. A collection of 398 yeast strains has been obtained using endemic and unique sources of fruit juices, industrial syrups, honey, and other high sugar content substrates, either natural or man made, products and by-products from Mexico. The osmotolerance of the strains was assessed by plate assay both in glucose (20-40-60%w/w). Strains were classified according to their osmotolerance in low, medium or highly tolerant to high glucose concentrations. The purified cultures were tested by their ability to growth in a solid plate media or liquid media of Yeas Nitrogen Base (YNB), added with specific monosaccharides as sole carbon source (glucose, galactose, lactose and fructose). Selected strains were subsequently tested in fermentation experiments with mixtures of two monosaccharides (galactose/glucose and glucose/fructose). Their ability to grow and selectively catabolize one monosaccharide was evaluated. Growth, fermentation activity and products of metabolism were determined by plate counts, CO2 production, turbidity and chromatographic analysis by HPLC. Selective catabolism of one monosaccharide in liquid media containing two monosaccharides was confirmed for 8 strains. Ion Exchange chromatographic processes were used in production of high fructose or galactose syrup. Laboratory scale processes for the production of fructose or galactose enriched syrups is now feasible, with important applications in food (like high fructose syrup as edulcorant) and fermentation technology (for GOS production).

Keywords: osmotolerant yeasts, selective metabolism, fructose syrup, GOS

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Authors: Karissa Graham, Andrew Campbell-Lloyd

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The deep inferior epigastric artery perforator flap (DIEP) is used to reconstruct large volumes of tissue. The DIEP flap is based on the deep inferior epigastric artery (DIEA) and vein. Accurate knowledge of the anatomy of these vessels allows for efficient dissection of the flap, minimal damage to surrounding tissue, and a well vascularized flap. A 54 year old lady was assessed for bilateral delayed autologous reconstruction with DIEP free flaps. The right DIEA was consistent with the described anatomy. The left DIEA had a vessel branching shortly after leaving the external iliac artery and before entering the muscle. This independent branch entered the muscle and had a long intramuscular course to the largest perforator. The main DIEA vessel demonstrated a type II branching pattern but had perforators that were too small to have a viable DIEP flap. There were no communicating arterial branches between the independent vessel and DIEA, however, there was one venous communication between them. A muscle sparing transverse rectus abdominis muscle flap was raised using the main periumbilical perforator from the independent vessel. Our case report demonstrated an unreported anatomical variant of the DIEA. A few anatomical variants have been described in the literature, including a unilateral absent DIEA and peritoneal-cutaneous perforators that had no connection to the DIEA. Doing a pre-operative CTA helps to identify these rare anatomical variations, which leads to safer, more efficient, and effective operating.

Keywords: aberrant anatomy, CT angiography, DIEP anatomy, free flap

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Authors: Kwangmin Joo

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Automatic detection of lumbar vertebrae and classification method is proposed for evaluating the degree of disc narrowing. Prior to classification, deep learning based segmentation is applied to detect individual lumbar vertebra. M-net is applied to segment five lumbar vertebrae and fine-tuning segmentation is employed to improve the accuracy of segmentation. Using the features extracted from previous step, clustering technique, k-means clustering, is applied to estimate the degree of disc space narrowing under four grade scoring system. As preliminary study, techniques proposed in this research could help building an automatic scoring system to diagnose the severity of disc narrowing from X-ray images.

Keywords: Disc space narrowing, Degenerative disc disorders, Deep learning based segmentation, Clustering technique

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Authors: Nor Zaidi Haron, Fauziyah Salehuddin, Norsuhaidah Arshad, Sani Irwan Salim

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Resistive random access memories (RRAMs) are one of the main candidates for future computer memories. However, due to their tiny size and immature device technology, the quality of the outgoing RRAM chips is seen as a serious issue. Defective RRAM cells might behave differently than existing semiconductor memories (Dynamic RAM, Static RAM, and Flash), meaning that they are difficult to be detected using existing test schemes. This paper presents an enhanced test scheme, referred to as Programmable Short Write Time (PSWT) that is able to improve the detection of faulty RRAM cells. It is developed by applying multiple weak write operations, each with different time durations. The test circuit embedded in the RRAM chip is made programmable in order to supply different weak write times during testing. The RRAM electrical model is described using Verilog-AMS language and is simulated using HSPICE simulation tools. Simulation results show that the proposed test scheme offers better open-resistive fault detection compared to existing test schemes.

Keywords: memory fault, memory test, design-for-testability, resistive random access memory

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Authors: Ashish Kumar, Tejendra Dixit, I. A. Palani, Vipul Singh

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Zinc oxide, with its interesting properties such as large band gap (3.37eV), high exciton binding energy (60 meV) and intense UV absorption has been studied in literature for various applications viz. optoelectronics, biosensors, UV-photodetectors etc. The performance of ZnO devices is highly influenced by morphologies, size, crystallinity of the ZnO active layer and processing conditions. Recently, our group has shown the influence of the in situ addition of KMnO4 in the precursor solution during the hydrothermal growth of ZnO nanorods (NRs) on their near band edge (NBE) emission. In this paper, we have investigated the effect of post-growth annealing on the variations in NBE and deep level (DL) emissions of as grown ZnO nanorods. These observed results have been explained on the basis of X-ray Diffraction (XRD) and Raman spectroscopic analysis, which clearly show that improved crystalinity and quantum confinement in ZnO nanorods.

Keywords: ZnO, nanorods, hydrothermal, KMnO4

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Authors: Zhang Tianping, Jia Yanhui, Li Juan, Yang Le, Yang Hao, Yang Wei, Sun Xiaojing, Shi Kai, Li Xingda, Sun Yunkui

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Lanzhou Institute of Physics (LIP) is the major supplier of electric propulsion subsystems for Chinese satellite platforms. The development statuses of these electric propulsion subsystems were summarized including the LIPS-200 ion electric propulsion subsystem (IEPS) for DFH-3B platform, the LIPS-300 IEPS for DFH-5 and DFH-4SP platform, the LIPS-200+ IEPS for DFH-4E platform and near-earth asteroid exploration spacecraft, the LIPS-100 IEPS for small satellite platform, the LHT-100 hall electric propulsion subsystem (HEPS) for flight test on XY-2 satellite, the LHT-140 HEPS for large LEO spacecraft, the LIPS-400 IEPS for deep space exploration mission and other EPS for other Chinese spacecraft.

Keywords: ion electric propulsion, hall electric propulsion, satellite platform, LIP

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Authors: Zahra Khoshnood, Mehdi Kazaie, Sajedeh Neisi

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In 2013, 24 fish samples were taken from two fishery regions in the north of Persian Gulf near the Iranian coastal lines. The two flatfishes were Yellofin seabream (Acanthopagrus latus) and Longtail tuna (Thannus tonggol). We analyzed total Hg concentration of liver and muscle tissues by Mercury Analyzer (model LECO AMA 254). The average concentration of total Hg in edible Muscle tissue of deep-Flounder was measured in Bandar-Abbas and was found to be 18.92 and it was 10.19 µg.g-1 in Bandar-Lengeh. The corresponding values for Oriental sole were 8.47 and 0.08 µg.g-1. The average concentration of Hg in liver tissue of deep-Flounder, in Bandar-Abbas was 25.49 and that in Bandar-Lengeh was 12.52 µg.g-1.the values for Oriental sole were 11.88 and 3.2 µg.g-1 in Bandar-Abbas and Bandar-Lengeh, respectively.

Keywords: mercury, Acanthopagrus latus, Thannus tonggol, Persian Gulf

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Authors: Joon-Yeop Na, Sang-Keun Baik, Kyu-Soo Chong

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Road sign sizes are related to their support and foundation, and the large-scale support that is generally installed at roadsides can cause inconvenience to pedestrians and damage the urban landscape. The most influential factor in determining the support and foundation of road signs is the wind load. In this study, we introduce a hole-type road sign to analyze its effects on reducing wind load. A hole-type road sign reduces the drag coefficient that is applied when considering the air and fluid resistance of a plate when the wind pressure is calculated, thus serving as an effective option for lightening the weights of road sign structures. A hole-type road sign is punctured with a perforator. Furthermore, the size of the holes and their distance is determined considering the damage to characters, the poor performance of reflective sheets, and legibility. For the calculation of the optimal specification of a hole-type road sign, we undertook a theoretical examination for reducing the wind loads on hole-type road signs, and analyzed the bending and reflectivity of sample road sign plates. The analytic results confirmed that a hole-type road sign sample that contains holes of 6 mm in diameter with a distance of 18 mm between the holes shows reflectivity closest to that of existing road signs; moreover, the average bending moment resulted in a reduction of 4.24%, and the support’s diameter is reduced by 40.2%.

Keywords: hole type, road sign, weight lightening, wind load

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Authors: Khadija Bouzaachane, El Mahdi El Guarmah

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The classification of low-resolution satellite images has been a worthwhile and fertile field that attracts plenty of researchers due to its importance in monitoring geographical areas. It could be used for several purposes such as disaster management, military surveillance, agricultural monitoring. The main objective of this work is to classify efficiently and accurately low-resolution satellite images by using novel technics of deep learning and reinforcement learning. The images include roads, residential areas, industrial areas, rivers, sea lakes, and vegetation. To achieve that goal, we carried out experiments on the sentinel-2 images considering both high accuracy and efficiency classification. Our proposed model achieved a 91% accuracy on the testing dataset besides a good classification for land cover. Focus on the parameter precision; we have obtained 93% for the river, 92% for residential, 97% for residential, 96% for the forest, 87% for annual crop, 84% for herbaceous vegetation, 85% for pasture, 78% highway and 100% for Sea Lake.

Keywords: classification, deep learning, reinforcement learning, satellite imagery

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Authors: Kadir Akkuş, Burcu A. Hamat, Kaan Ciloglu

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Additive Manufacturing (AM) is the respectable improvement of this century in the field of manufacturing and regarded as a breakthrough that represents the third industrial revolution by the leading authorities such as Wohlers Associates Inc., The Economist, and MIT Technology Review. Thanks to the stacking and unifying methodology of AM, design of lighter but stiffer parts with really more complex shapes and geometrical features, which were not possible by traditional subtractive manufacturing methods, became achievable. Through analysis of the AM process must be performed and mechanical properties of manufactured test parts must be studied to provide input for design. Furthermore, process capabilities, constraints, limitations and challenges regarding AM must be examined so that the design must be compatible with the process to be able to take all the advantages of the AM. In this paper, capabilities and limitations of AM will be investigated through a test part including unique features and manufactured from Ti-6Al-4V by employing Electron Beam Melting (EBM) technology by comparing to the test parts introduced in literature.

Keywords: additive manufacturing, DfAM, EBM, test artifact, Ti-6Al-4V

Procedia PDF Downloads 119

Authors: M. Iqbal Mahmud, Haeng Muk Cho, Seo Hyun Sang, Wang Wen Hai, Chang Heon Yi, Man Ik Hwang, Dae Hoon Kang

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Solenoid operated electromagnetic control valve (ECV) playing an important role for car’s air conditioning control system. ECV is used in external variable displacement swash plate type compressor and controls the entire air conditioning system by means of a pulse width modulation (PWM) input signal supplying from an external source (controller). Complete form of ECV contains number of internal features like valve body, core, valve guide, plunger, guide pin, plunger spring, bellows etc. While designing the ECV; dimensions of different internal items must meet the standard requirements as it is quite challenging. In this research paper, especially the dimensioning of ECV body and its three pressure ports through which the air/refrigerant passes are considered. Here internal leakage test analysis of ECV body is being carried out from its discharge port (Pd) to crankcase port (Pc) when the guide valve is placed inside it. The experiments have made both in ordinary and digital system using different assumptions and thereafter compare the results.

Keywords: electromagnetic control valve (ECV), leakage, pressure port, valve body, valve guide

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Authors: Girlie D. Leopoldo, Myrna S. Ceniza, Ronnie L. Besagas, Antonio Y. Asoy, Noel T. Dael, Romeo M. Del Rosario

Abstract:

The quality of groundwater from main deep well sources of seven (7) municipalities in Western Misamis Oriental, Philippines was examined. The study looks at the well waters’ physicochemical properties (temperture, pH, turbidity, conductivity, TDS, salinity, chlorides, TOC, and total hardness), the heavy metals and other metals (Pb, Cd, Al, As, Hg, Sb, Zn, Cu, Fe) and their microbiological (total coliform and E. coli) characteristics. The physicochemical properties of groundwater samples were found to be within the Philippine National Standards for Drinking Water (PNSDW)/US-EPA except for the TDS, chlorides, and hardness of some sources. Well waters from both Initao and Gitagum municipalities have TDS values of 643.2 mg/L and 578.4 mg/L, respectively, as compared to PNSDW/US-EPA standard limit of 500 mg/L. These same two municipalities Initao and Gitagum as well as the municipality of Libertad also have chloride levels beyond the 250 mg/L limit of PNSDW/US-EPA/EU with values at 360, 318 and 277 mg/L respectively. The Libertad sample also registered a total hardness of 407.5 mg/L CaCO3 as compared to the 300 mg/L PNSDW limit. These mentioned three (3) municipalities are noticed to have similar geologic structures. Although metal analyses revealed the presence of Zn, Cu and Fe in almost all well water sources, their concentrations are below allowable limit. All well waters from the seven municipalities failed in total coliform count. Escherichia coli were also found in well waters from four (4) municipalities including Laguindingan, Lugait, Gitagum, and Libertad. The presence of these pathogens in the well waters needs to be addressed to make the waters suitable for human consumption.

Keywords: groundwater, deep well, physico-chemical, heavy metal, microbiological

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Authors: Esra Güney, Tuba Uçar

Abstract:

Aim: This study has been conducted for the purpose of determining the effects of fetal movement counting on antenatal maternal attachment. Material and Method: This research was conducted on the basis of the real test model with the pre-test /post-test control groups. The study population consists of pregnant women registered in the six different Family Health Centers located in the central Malatya districts of Yeşilyurt and Battalgazi. When power analysis is done, the sample size was calculated for each group of at least 55 pregnant women (55 tests, 55 controls). The data were collected by using Personal Information Form and MAAS (Maternal Antenatal Attachment Scale) between July 2015-June 2016. Fetal movement counting training was given to pregnant women by researchers in the experimental group after the pre-test data collection. No intervention was applied to the control group. Post-test data for both groups were collected after four weeks. Data were evaluated with percentage, chi-square arithmetic average, chi-square test and as for the dependent and independent group’s t test. Result: In the MAAS, the pre-test average of total scores in the experimental group is 70.78±6.78, control group is also 71.58±7.54 and so there was no significant difference in mean scores between the two groups (p>0.05). MAAS post-test average of total scores in the experimental group is 78.41±6.65, control group is also is 72.25±7.16 and so the mean scores between groups were found to have statistically significant difference (p<0.05). Conclusion: It was determined that fetal movement counting increases the maternal antenatal attachments.

Keywords: antenatal maternal attachment, fetal movement counting, pregnancy, midwifery

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Authors: Abdul Qader Melhm, Hussein Elrafidi

Abstract:

This paper is dealing with studying the structural behavior of a steel-composite hollow reinforced concrete (RC) column model under combined eccentric loading. The composite model consists of an inner steel tube surrounded via a concrete core with longitudinal and circular transverse reinforcement. The radius of gyration according to American and Euro specifications be calculated, in order to calculate the thinnest ratio for this type of composite column model, in addition to the flexural rigidity. Formulas for interaction diagram is given for this type of model, which is a general loading conditions in which an element is exposed to an axial load with bending at the same time. The structural capacity of this model, elastic, plastic loads and strains will be computed and compared with experimental results. The total eccentric axial load of the column model is calculated based on the effective length KL available from several relationships provided in the paper. Furthermore, the inner tube experiences buckling failure after reaching its maximum strength will be investigated.

Keywords: column, composite, eccentric, inner tube, interaction, reinforcement

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Authors: Ira Banoth, Anil Agarwal

Abstract:

In this study, bond behavior between galvanized steel and concrete at elevated temperatures was studied in the temperature range of 20-500 o C. A 12 mm diameter of galvanized rebar is used for the bond test. A heating rate of 2 o C/min is used for heating the specimen until the desired interface temperature is reached. The beam test is conducted to represent the bond behavior of flexural members in reinforced concrete structures. The heating protocol is the high-temperature test. The high-temperature test is the test where the specimen is heated by following a heating rate of 2 o C/min until the desired temperature reaches the steel-concrete interface, and then the mechanical load is applied until the specimen fails. The specimen will fail within 2 minutes of load application, so the temperature variation will not be very much at the steel-concrete interface. The bond strength will be decreased with the increase in temperatures. The absolute values of bond strength vary from 14.7 to 9.5 MPa in the temperature range of 20 to 500 o C. The reduction of bond strength varies from 100 % to 64.6 % in the temperatures range of 100-500 o C.

Keywords: galvanized steel, concrete, elevated temperatures, beam test, heating rate, bond strength

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