Search results for: surface damage detection

Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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Authors: Jaeyoung Kim, Heeju Lee, Huijin Jung, Heesoo Pyo, Seungki Kim, Joonseok Lee

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Avian influenza viruses (AIV) are the primary cause of highly contagious respiratory diseases caused by type A influenza viruses of the Orthomyxoviridae family. AIV are categorized on the basis of types of surface glycoproteins such as hemagglutinin and neuraminidase. Certain H5 and H7 subtypes of AIV have evolved to the high pathogenic avian influenza (HPAI) virus, which has caused considerable economic loss to the poultry industry and led to severe public health crisis. Several commercial kits have been developed for on-site detection of AIV. However, the sensitivity of these methods is too low to detect low virus concentrations in clinical samples and opaque stool samples. Here, we introduced a background-free near-infrared (NIR)-to-NIR upconversion nanoparticle-based lateral flow immunoassay (NNLFA) platform to yield a sensor that detects AIV within 20 minutes. Ca²⁺ ion in the shell was used to enhance the NIR-to-NIR upconversion photoluminescence (PL) emission as a heterogeneous dopant without inducing significant changes in the morphology and size of the UCNPs. In a mixture of opaque stool samples and gold nanoparticles (GNPs), which are components of commercial AIV LFA, the background signal of the stool samples mask the absorption peak of GNPs. However, UCNPs dispersed in the stool samples still show strong emission centered at 800 nm when excited at 980 nm, which enables the NNLFA platform to detect 10-times lower viral load than a commercial GNP-based AIV LFA. The detection limit of NNLFA for low pathogenic avian influenza (LPAI) H5N2 and HPAI H5N6 viruses was 10² EID₅₀/mL and 10³.⁵ EID₅₀/mL, respectively. Moreover, when opaque brown-colored samples were used as the target analytes, strong NIR emission signal from the test line in NNLFA confirmed the presence of AIV, whereas commercial AIV LFA detected AIV with difficulty. Therefore, we propose that this rapid and background-free NNLFA platform has the potential of detecting AIV in the field, which could effectively prevent the spread of these viruses at an early stage.

Keywords: avian influenza viruses, lateral flow immunoassay on-site detection, upconversion nanoparticles

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Authors: Abigail M. Csik, Gabriel A. Radvansky

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As people read through event-based narratives, they construct an event model that captures information about the characters, goals, location, time, and causality. For many reasons, memory for such narratives is represented at different levels, namely, the surface form, textbase, and event model levels. Rereading has been shown to decrease surface form memory, while, at the same time, increasing textbase and event model memories. More generally, distributed practice has consistently shown memory benefits over massed practice for different types of materials, including texts. However, little research has investigated distributed practice of narratives at different inter-study intervals and these effects on these three levels of memory. Recent work in our lab has indicated that there may be dramatic changes in patterns of forgetting around one week, which may affect the three levels of memory. The present experiment aimed to determine the effects of rereading on the three levels of memory as a factor of whether the texts were reread before versus after one week. Participants (N = 42) read a set of stories, re-read them either before or after one week (with an inter-study interval of three days, seven days, or fourteen days), and then took a recognition test, from which the three levels of representation were derived. Signal detection results from this study reveal that differential patterns at the three levels as a factor of whether the narratives were re-read prior to one week or after one week. In particular, an ANOVA revealed that surface form memory was lower (p = .08) while textbase (p = .02) and event model memory (p = .04) were greater if narratives were re-read 14 days later compared to memory when narratives were re-read 3 days later. These results have implications for what type of memory benefits from distributed practice at various inter-study intervals.

Keywords: memory, event cognition, distributed practice, consolidation

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Authors: Mohammad Sarchami, Mohsen Zeinalkhani

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Always, financial reporting system faces some problems to win public ear. The increase in the number of fraud and representation, often combined with the bankruptcy of large companies, has raised concerns about the quality of financial statements. So, investors, legislators, managers, and auditors have focused on significant fraud detection or prevention in financial statements. This article aims to investigate the Sugeno fuzzy classification to consider fraud detection in financial reporting of accepted firms by Tehran stock exchange. The hypothesis is: Sugeno fuzzy classification may detect fraud in financial reporting by financial ratio. Hypothesis was tested using Matlab software. Accuracy average was 81/80 in Sugeno fuzzy classification; so the hypothesis was confirmed.

Keywords: fraud, financial reporting, Sugeno fuzzy classification, firm

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Authors: Farokh Alipour, Ali Falavand, Neda Beit Saeid

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The calculation of the effect of accidental releases of flammable materials such as LNG requires the use of a suitable consequence model. This study is due to providing a planning advice for developments in the vicinity of LNG sites and other sites handling flammable materials. In this paper, an applicable algorithm that is able to model pool fires on water is presented and applied to estimate pool fire damage zone. This procedure can be used to model pool fires on land and could be helpful in consequence modeling and domino effect zone measurements of flammable materials which is needed in site selection and plant layout.

Keywords: LNG, pool fire, spill, radiation

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Authors: Ergün Şakalar, Şeyma Özçirak Ergün

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Pistachio nuts, the fruits of the pistachio tree (Pistacia vera), are edible tree nuts highly valued for their organoleptic properties. Pistachio nuts used in snack foods, chocolates, baklava, meat products, ice-cream industries and other gourmet products as ingredients. Undeclared pistachios may be present in food products as a consequence of fraudulent substitution. Control of food samples is very important for safety and fraud. Mix of pistachio, peanut (Arachis hypogaea), pea (Pisum sativum L.) used instead of pistachio in food products, because pistachio is a considerably expensive nut. To solve this problem, a sensitive polymerase chain reaction PCR has been developed. A real-time PCR assay for the detection of pea, peanut and pistachio in baklava was designed by using EvaGreen fluorescence dye. Primers were selected from powerful regions for identification of pea, peanut and pistachio. DNA from reference samples and industrial products were successfully extracted with the GIDAGEN® Multi-Fast DNA Isolation Kit. Genomes were identified based on their specific melting peaks (Mp) which are 77°C, 85.5°C and 82.5°C for pea, peanut and pistachio, respectively. Homogenized mixtures of raw pistachio, pea and peanut were prepared with the ratio of 0.01%, 0.1%, 1%, 10%, 40% and 70% of pistachio. Quantitative detection limit of assay was 0.1% for pistachio. Also, real-time PCR technique used in this study allowed the qualitative detection of as little as 0.001% level of peanut DNA, 0,000001% level of pistachio DNA and 0.000001% level of pea DNA in the experimental admixtures. This assay represents a potentially valuable diagnostic method for detection of nut species adulterated with pistachio as well as for highly specific and relatively rapid detection of small amounts of pistachio in food samples.

Keywords: pea, peanut, pistachio, real-time PCR

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Authors: Ryu Wonjin, Choi Hyeok, Park Joonhong

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Overlay welding for improving surface properties is a method of the surface treatments which improve surface properties of material by welding materials of alloy having corrosion resistance on the basic material surface. Overlay welding affects contents of chemical components and weld hardness from different parts by dilution of the lamination layer thickness, and it determines surface properties. Therefore, overlay welding has to take into account thickness of the lamination layers with the process. As a result in this study examined contents of Fe, weldability of the base metal and monel materials, hardness and surface flatness from different parts according to each the lamination layer parameters by overlay welding monel materials with corrosion resources to the base material of carbon steel. Through this, evaluated effect by the lamination layer parameters of welding and presented decision methods of the lamination layer parameters of the overlay welding by the purpose of use.

Keywords: clad pipe, lamination layer parameters, monel, overlay welding

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Authors: Garance Liaboeuf, Alain Le Bot, Ali Daouadji, Antoine Martinet, Mohamed Bouteldja, Nicolas Grignard, Damien Pilet

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As every French road operator, Autoroutes et Tunnel du Mont Blanc (ATMB) conducts annual inspections of its infrastructures. Significant loss of skid resistance has been observed on some sections of his network, sometimes on recent pavements. In the way of making the mechanisms and factors that can lead to this loss of grip more understandable, ATMB has launched a study aimed at identifying the causes and developing solutions to prevent this phenomenon. To quantify the deterioration of different road surfaces subjected to controlled scraping with steel blades of snow removal machines, a field campaign was conducted. These operations are carried out during the winter period according to a strict protocol. In order to correct the skid-resistance values, a control panel is set up. In this way, only the effect of the scraping is taken into account. It allows us to exclude the influence of the environment (temperature, humidity, etc.) and of the surface state on the skid resistance values measured during the different sessions. Skid measurements after eight years of scraping cycles showed a 7% to 13% decrease in microtexture and a 2% to 12% decrease in macrotexture adhesion. These reductions are attributed to the phenomenon of polishing road surfaces by using steel blades. Also, regeneration phenomena occur after a certain number of blades pass. Differences in steel scraper blade resistance appear related to the intrinsic properties of the aggregate used in the pavement formulation and its type. Finally, the results of this campaign will allow the determination of the resistance characteristics of the pavement damage by the steel blade of snow plows. An evolution law of the surface condition as a function of the scraping operations will also be developed from this study.

Keywords: pavement, skid, surface, snow plow

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Authors: Shanshan Guo, Xiaoying Zhu, Dominik Jańczewski, Koon Gee Neoh

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Surface charge and wettability are two prominent physical factors governing cell adhesion and have been extensively studied in the literature. However, a comparison between the two driving forces in terms of their independent and cooperative effects in affecting cell adhesion is rarely explored on a systematic and quantitative level. Herein, we formulate a protocol which allows two-dimensional and independent control over both surface charge and wettability. This protocol enables the unambiguous comparison of the effects of these two properties on cell adhesion. This strategy is implemented by controlling both the relative thickness of polyion layers in the layer-by-layer assembly and the polyion side chain chemical structures. The 2D property matrix spans surface isoelectric point ranging from 5 to 9 and water contact angle from 35º to 70º, with other interferential factors (e.g. roughness) eliminated. The interplay between these two surface variables influences 3T3 fibroblast cell adhesion. The results show that both surface charge and wettability have an effect on its adhesion. The combined effects of positive charge and hydrophilicity led to the highest cell adhesion whereas negative charge and hydrophobicity led to the lowest cell adhesion. Our design strategy can potentially form the basis for studying the distinct behaviors of electrostatic force or wettability driven interfacial phenomena and serving as a reference in future studies assessing cell adhesion to surfaces with known charge and wettability within the property range studied here.

Keywords: cell adhesion, layer-by-layer, surface charge, surface wettability

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Authors: Amira Shakila Razali, Faridah Lisa Supian, Muhammad Mat Salleh, Suriani Abu Bakar

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Water contamination by toxic compound is one of the serious environmental problems today. These toxic compounds mostly originated from industrial effluents, agriculture, natural sources and human waste. These study are focused on modification of multiwalled carbon nanotube (MWCNTs) with nanoparticle of calixarene and explore the possibility of using this nanocomposites for the remediation of cadmium in water. The nanocomposites were prepared by dissolving calixarene in chloroform solution as solvent, followed by additional multiwalled carbon nanotube (MWCNTs) then sonication process for 3 hour and fabricated the nanocomposites on substrate by spin coating method. Finally, the nanocomposites were tested on cadmium ion (10 mg/ml). The morphology of nanocomposites was investigated by FESEM showing the formation of calixarene on the outer walls of carbon nanotube and cadmium ion also clearly seen from the micrograph. This formation was supported by using energy dispersive x-ray (EDX). The presence of cadmium ions in the films, leads to some changes in the surface potential and Fourier Transform Infrared spectroscopy (FTIR).This nanocomposites have potential for development of sensor for pollutant monitoring and nanoelectronics devices applications

Keywords: calixarene, multiwalled carbon nanotubes, cadmium, surface potential

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Authors: Xiang Yu, Chuntao Feng, Lu Yang, Meiyang Song, Wenhao Zhou

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The existing two-dimensional micro-Doppler features extraction ignores the correlation information between the spatial and temporal dimension features. For the range-Doppler map, the time dimension is introduced, and a frequency modulation continuous wave (FMCW) radar human fall detection algorithm based on time-varying range-Doppler features is proposed. Firstly, the range-Doppler sequence maps are generated from the echo signals of the continuous motion of the human body collected by the radar. Then the three-dimensional data cube composed of multiple frames of range-Doppler maps is input into the three-dimensional Convolutional Neural Network (3D CNN). The spatial and temporal features of time-varying range-Doppler are extracted by the convolution layer and pool layer at the same time. Finally, the extracted spatial and temporal features are input into the fully connected layer for classification. The experimental results show that the proposed fall detection algorithm has a detection accuracy of 95.66%.

Keywords: FMCW radar, fall detection, 3D CNN, time-varying range-doppler features

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Authors: Elsayed Amer, Tarek Essam, Abdullah Hella, Mohammed Al-Ajmi

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Hydrocarbon production decline in mature gas fields is inevitable, and mitigating these circumstances is essential to ensure a longer production period. Production decline is not only influenced by reservoir pressure and wellbore integrity; however, associated liquids in the reservoir rock have a considerable impact on the production process. The associated liquid may result in liquid loading, near wellbore damage, condensate banking, fine sand migration, and wellhead pressure depletion. Consequently, the producing well will suffocate, and the liquid column will seize the well from flowing. A common solution in such circumstances is reducing the surface pressure by opening the well to the atmospheric pressure and flaring the produced liquids. This practice may not be applicable to many cases since the atmospheric pressure is not low enough to create a sufficient driving force to flow the well. In addition, flaring the produced hydrocarbon is solving the issue on account of the environment, which is against the world's efforts to mitigate the impact of climate change. This paper presents a novel approach and a case study that utilizes a multi-phase mobile wellhead gas compression unit (MMWGC) to reduce surface pressure to the sub-atmospheric level and transfer the produced hydrocarbons to the sales line. As a result, the liquid column will unload in a zero-flaring manner, and the life of the producing well will extend considerably. The MMWGC unit was able to successfully kick off a dead well to produce up to 10 MMSCFD after reducing the surface pressure for 3 hours. Applying such novelty on a broader scale will not only extend the life of the producing wells yet will also provide a zero-flaring, economically and environmentally preferred solution.

Keywords: petroleum engineering, zero-flaring, liquid loading, well revival

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Authors: Weitao Lin

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To quickly extract adequate information from large-scale unstructured text data, this paper studies the representation of events in Chinese scenarios and performs the regularized abstraction. It proposes a Chinese event detection technique based on dependency parsing and rule matching. The method first performs dependency parsing on the original utterance, then performs pattern matching at the word or phrase granularity based on the results of dependent syntactic analysis, filters out the utterances with prominent non-event characteristics, and obtains the final results. The experimental results show the effectiveness of the method.

Keywords: natural language processing, Chinese event detection, rules matching, dependency parsing

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Authors: Xiaoyan Dai, Hsieh Yisan

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Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

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Authors: Hoshang Kolivand, Mahyar Kolivand, Mohd Shahrizal Sunar, Mohd Azhar M. Arsad

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Real-time shadow generation in virtual environments and Augmented Reality (AR) was always a hot topic in the last three decades. Lots of calculation for shadow generation among AR needs a fast algorithm to overcome this issue and to be capable of implementing in any real-time rendering. In this paper, a silhouette detection algorithm is presented to generate shadows for AR systems. Δ+ algorithm is presented based on extending edges of occluders to recognize which edges are silhouettes in the case of real-time rendering. An accurate comparison between the proposed algorithm and current algorithms in silhouette detection is done to show the reduction calculation by presented algorithm. The algorithm is tested in both virtual environments and AR systems. We think that this algorithm has the potential to be a fundamental algorithm for shadow generation in all complex environments.

Keywords: silhouette detection, shadow volumes, real-time shadows, rendering, augmented reality

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Authors: Jarek Krajewski, David Daxberger

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We propose a stress detection method based on an RGB camera using heart rate detection, also known as Photoplethysmography Imaging (PPGI). This technique focuses on the measurement of the small changes in skin colour caused by blood perfusion. A stationary lab setting with simulated video conferences is chosen using constant light conditions and a sampling rate of 30 fps. The ground truth measurement of heart rate is conducted with a common PPG system. The proposed approach for pulse peak detection is based on a machine learning-based approach, applying brute force feature extraction for the prediction of heart rate pulses. The statistical analysis showed good agreement (correlation r = .79, p<0.05) between the reference heart rate system and the proposed method. Based on these findings, the proposed method could provide a reliable, low-cost, and contactless way of measuring HR parameters in daily-life environments.

Keywords: heart rate, PPGI, machine learning, brute force feature extraction

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Authors: Moustafa Osman Mohammed

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This paper introduces topological order in descried social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. Topological order is important in describing the physical systems for exploiting optical systems and improving photonic devices. The stats of topological order have some interesting properties of topological degeneracy and fractional statistics that reveal the entanglement origin of topological order, etc. Topological ideas in photonics form exciting developments in solid-state materials, that being; insulating in the bulk, conducting electricity on their surface without dissipation or back-scattering, even in the presence of large impurities. A specific type of autopoiesis system is interrelated to the main categories amongst existing groups of the ecological phenomena interaction social and medical sciences. The hypothesis, nevertheless, has a nonlinear interaction with its natural environment 'interactional cycle' for exchange photon energy with molecules without changes in topology. The engineering topology of a biosensor is based on the excitation boundary of surface electromagnetic waves in photonic band gap multilayer films. The device operation is similar to surface Plasmonic biosensors in which a photonic band gap film replaces metal film as the medium when surface electromagnetic waves are excited. The use of photonic band gap film offers sharper surface wave resonance leading to the potential of greatly enhanced sensitivity. So, the properties of the photonic band gap material are engineered to operate a sensor at any wavelength and conduct a surface wave resonance that ranges up to 470 nm. The wavelength is not generally accessible with surface Plasmon sensing. Lastly, the photonic band gap films have robust mechanical functions that offer new substrates for surface chemistry to understand the molecular design structure and create sensing chips surface with different concentrations of DNA sequences in the solution to observe and track the surface mode resonance under the influences of processes that take place in the spectroscopic environment. These processes led to the development of several advanced analytical technologies: which are; automated, real-time, reliable, reproducible, and cost-effective. This results in faster and more accurate monitoring and detection of biomolecules on refractive index sensing, antibody-antigen reactions with a DNA or protein binding. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other in order to form unique spatial structure and dynamics of biological molecules for providing the environment mutual contribution in investigation of changes due to the pathogenic archival architecture of cell clusters.

Keywords: autopoiesis, photonics systems, quantum topology, molecular structure, biosensing

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Authors: Alireza Lohrasbi, Alireza Lavaei, Mohammadali M. Shahlaei

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The liquid flow and the free surface shape during the initial stage of dam breaking are investigated. A numerical scheme is developed to predict the wave of an unsteady, incompressible viscous flow with free surface. The method involves a two dimensional finite element (2D), in a vertical plan. The Naiver-Stokes equations for conservation of momentum and mass for Newtonian fluids, continuity equation, and full nonlinear kinematic free-surface equation were used as the governing equations. The mapping developed to solve highly deformed free surface problems common in waves formed during wave propagation, transforms the run up model from the physical domain to a computational domain with Arbitrary Lagrangian Eulerian (ALE) finite element modeling technique.

Keywords: dam break, Naiver-Stokes equations, free-surface flows, Arbitrary Lagrangian-Eulerian

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Authors: Pola Goldberg Oppenheimer, Stephan Hofmann, Sumeet Mahajan

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Owing to its fingerprint molecular specificity and high sensitivity, surface-enhanced Raman scattering (SERS) is an established analytical tool for chemical and biological sensing capable of single-molecule detection. A strong Raman signal can be generated from SERS-active platforms given the analyte is within the enhanced plasmon field generated near a noble-metal nanostructured substrate. The key requirement for generating strong plasmon resonances to provide this electromagnetic enhancement is an appropriate metal surface roughness. Controlling nanoscale features for generating these regions of high electromagnetic enhancement, the so-called SERS ‘hot-spots’, is still a challenge. Significant advances have been made in SERS research, with wide-ranging techniques to generate substrates with tunable size and shape of the nanoscale roughness features. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for miniaturised sensing devices. Carbon nanotubes (CNTs) have been concurrently, a topic of extensive research however, their applications for plasmonics has been only recently beginning to gain interest. CNTs can provide low-cost, large-active-area patternable substrates which, coupled with appropriate functionalization capable to provide advanced SERS-platforms. Herein, advanced methods to generate CNT-based SERS active detection platforms will be discussed. First, a novel electrohydrodynamic (EHD) lithographic technique will be introduced for patterning CNT-polymer composites, providing a straightforward, single-step approach for generating high-fidelity sub-micron-sized nanocomposite structures within which anisotropic CNTs are vertically aligned. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements with each of the EHD-CNTs individual structural units functioning as an isolated sensor. Further, gold-functionalized VACNTFs are fabricated as SERS micro-platforms. The dependence on the VACNTs’ diameters and density play an important role in the Raman signal strength, thus highlighting the importance of structural parameters, previously overlooked in designing and fabricating optimized CNTs-based SERS nanoprobes. VACNTs forests patterned into predesigned pillar structures are further utilized for multiplex detection of bio-analytes. Since CNTs exhibit electrical conductivity and unique adsorption properties, these are further harnessed in the development of novel chemical and bio-sensing platforms.

Keywords: carbon nanotubes (CNTs), EHD patterning, SERS, vertically aligned carbon nanotube forests (VACNTF)

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Authors: Shih-Wen Hsiao, Rong-Qi Chen, Chien-Yu Lin

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The topic of surface flattening plays a vital role in the field of computer aided design and manufacture. Surface flattening enables the production of 2D patterns and it can be used in design and manufacturing for developing a 3D surface to a 2D platform, especially in fashion design. This study describes surface flattening based on minimum energy methods according to the property of different fabrics. Firstly, through the geometric feature of a 3D surface, the less transformed area can be flattened on a 2D platform by geodesic. Then, strain energy that has accumulated in mesh can be stably released by an approximate implicit method and revised error function. In some cases, cutting mesh to further release the energy is a common way to fix the situation and enhance the accuracy of the surface flattening, and this makes the obtained 2D pattern naturally generate significant cracks. When this methodology is applied to a 3D mannequin constructed with feature lines, it enhances the level of computer-aided fashion design. Besides, when different fabrics are applied to fashion design, it is necessary to revise the shape of a 2D pattern according to the properties of the fabric. With this model, the outline of 2D patterns can be revised by distributing the strain energy with different results according to different fabric properties. Finally, this research uses some common design cases to illustrate and verify the feasibility of this methodology.

Keywords: surface flattening, strain energy, minimum energy, approximate implicit method, fashion design

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Authors: Y. S. Oh, P. Abhishesh, B. S. Ryuh

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This paper presents the method of trajectory planning by the robot end-effector which accounts for more accurate and smooth differential geometry of the ruled surface generated by tool line fixed with end-effector based on the methods of curvature theory of ruled surface and the dual curvature theory, and focuses on the underlying relation to unite them for enhancing the efficiency for trajectory planning. Robot motion can be represented as motion properties of the ruled surface generated by trajectory of the Tool Center Point (TCP). The linear and angular properties of the six degree-of-freedom motion of end-effector are computed using the explicit formulas and functions from curvature theory and dual curvature theory. This paper explains the complete dualization of ruled surface and shows that the linear and angular motion applied using the method of dual curvature theory is more accurate and less complex.

Keywords: dual curvature theory, robot end effector, ruled surface, TCP (Tool Center Point)

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Authors: Youhang Zhou, Weimin Zeng, Qi Xie

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Abstract: In order to solve the wear recognition problem of the machine tool guide surface, a new machine tool guide surface recognition method based on the radar-graph barycentre feature is presented in this paper. Firstly, the gray mean value, skewness, projection variance, flat degrees and kurtosis features of the guide surface image data are defined as primary characteristics. Secondly, data Visualization technology based on radar graph is used. The visual barycentre graphical feature is demonstrated based on the radar plot of multi-dimensional data. Thirdly, a classifier based on the support vector machine technology is used, the radar-graph barycentre feature and wear original feature are put into the classifier separately for classification and comparative analysis of classification and experiment results. The calculation and experimental results show that the method based on the radar-graph barycentre feature can detect the guide surface effectively.

Keywords: guide surface, wear defects, feature extraction, data visualization

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Authors: J. Hajnys, M. Pagac, J. Petru, P. Stefek, J. Mesicek, J. Kratochvil

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The new progressive method of 3D metal printing SLM (Selective Laser Melting) is increasingly expanded into the normal operation. As a result, greater demands are placed on the surface quality of the parts produced in this way. The article deals with research of selected finishing methods (tumbling, face milling, sandblasting, shot peening and brushing) and their impact on the final surface roughness. The 20 x 20 x 7 mm produced specimens using SLM additive technology on the Renishaw AM400 were subjected to testing of these finishing methods by adjusting various parameters. Surface parameters of roughness Sa, Sz were chosen as the evaluation criteria and profile parameters Ra, Rz were used as additional measurements. Optical measurement of surface roughness was performed on Alicona Infinite Focus 5. An experiment conducted to optimize the surface roughness revealed, as expected, that the best roughness parameters were achieved through a face milling operation. Tumbling is particularly suitable for 3D printing components, as tumbling media are able to reach even complex shapes and, after changing to polishing bodies, achieve a high surface gloss. Surface quality after tumbling depends on the process time. Other methods with satisfactory results are shot peening and tumbling, which should be the focus of further research.

Keywords: additive manufacturing, selective laser melting, SLM, surface roughness, stainless steel

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Authors: K. Padmavathi, K. Sri Ramakrishna

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This study describes a procedure for the detection of Left and Right Bundle Branch Block (LBBB and RBBB) ECG patterns using spectral Coherence(SC) technique and LM Neural Network. The Coherence function finds common frequencies between two signals and evaluate the similarity of the two signals. The QT variations of Bundle Blocks are observed in lead V1 of ECG. Spectral Coherence technique uses Welch method for calculating PSD. For the detection of normal and Bundle block beats, SC output values are given as the input features for the LMNN classifier. Overall accuracy of LMNN classifier is 99.5 percent. The data was collected from MIT-BIH Arrhythmia database.

Keywords: bundle block, SC, LMNN classifier, welch method, PSD, MIT-BIH, arrhythmia database

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Authors: Rui Wang, Shanfa Tang, Yuanwu Dong, Siyao Wang, Zhaowen Jiang, Di Han

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A sulfonate Gemini surfactant sodium N,N`-bis(tetradecanoyl) propanediamine dipropyl sulfonate (GNS-14) was synthesized from 1,3-propanediamine, tetradecanoyl chloride, and1,3-propanesulfonic lactone. GNS-14 was characterized by FT-IR, 1H NMR. The surface activity, interfacial activity, and emulsification properties of GNS-14 solution were systematically studied. The critical micelle concentration (CCMC) of GNS-14 surfactant was 0.056 mmol/L, and the surface tension (γCMC) was 18.2 mN/m; at 50℃, 0.5% GNS-14 solution can reduce the oil-water interfacial tension to 6.5×10−2 mN/m. GNS-14 has excellent surface activity, interfacial activity, and emulsifying properties.

Keywords: gemini surfactants, surface tension, low interfacial tension, emulsifying properties

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Authors: Anat Thanpinta

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This research aimed to study on the efficiency of wastewater treatment by comparing the different aeration times of surface aerators in Suan Sunandha Rajabhat University. In doing so, the operation of surface aerators was divided into 2 groups which included the groups of 8 hours (8-0/opened-closed) and 4 hours (2-2/opened-closed) of aeration time per day. As a result of the study, it was found that the efficiency of wastewater treatment in the forms of DO, BOD, turbidity and NO2- by 8 hours (8-0/opened-closed) and 4 hours (2-2/opened-closed) of aeration time per day of surface aerators was not statistically different [Sig. = .644, .488, .716 and .054 > α (.05)] while the efficiency in the forms of NO3- and P was significantly different at the statistical level of .01 [Sig. = .001 and .000 < α (.01)].

Keywords: aeration time, surface aerator, wastewater treatment, efficiency

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Authors: Binnur Sagbas

Abstract:

Artificial joint replacements such as total knee and total hip prosthesis have been applied to the patients who affected by osteoarthritis. Although different material combinations are used for these joints, biopolymers are most commonly preferred materials especially for acetabular cup and tibial component of hip and knee joints respectively. The main limitation that shortens the service life of these prostheses is wear. Wear is complicated phenomena and it must be considered with friction and lubrication. In this study, micro wave (MW) induced argon+oxygen plasma surface modification were applied on ultra-high molecular weight polyethylene (UHMWPE) and vitamin E blended UHMWPE (VE-UHMWPE) biopolymer surfaces to improve surface wettability and wear resistance of the surfaces. Contact angel measurement method was used for determination of wettability. Ball-on-disc wear test was applied under 25% bovine serum lubrication conditions. The results show that surface wettability and wear resistance of both material samples were increased by plasma surface modification.

Keywords: artificial joints, plasma surface modification, UHMWPE, vitamin E, wear

Procedia PDF Downloads 299

Authors: AlHanoof A. Alharbi, Fatima M. Alamoudi, Razan A. Albrahim, Sarah F. Alharbi, Abdullah M Almuhaideb, Norah A. Almubairik, Abdulrahman Alharby, Naya M. Nagy

Abstract:

Recently, drones received a rapid interest in different industries worldwide due to its powerful impact. However, limitations still exist in this emerging technology, especially privacy violation. These aircrafts consistently threaten the security of entities by entering restricted areas accidentally or deliberately. Therefore, this research project aims to develop drone detection and prevention mechanism to protect the restricted area. Until now, none of the solutions have met the optimal requirements of detection which are cost-effectiveness, high accuracy, long range, convenience, unaffected by noise and generalization. In terms of prevention, the existing methods are focusing on impractical solutions such as catching a drone by a larger drone, training an eagle or a gun. In addition, the practical solutions have limitations, such as the No-Fly Zone and PITBULL jammers. According to our study and analysis of previous related works, none of the solutions includes detection and prevention at the same time. The proposed solution is a combination of detection and prevention methods. To implement the detection system, a passive radar will be used to properly identify the drone against any possible flying objects. As for the prevention, jamming signals and forceful safe landing of the drone integrated together to stop the drone’s operation. We believe that applying this mechanism will limit the drone’s invasion of privacy incidents against highly restricted properties. Consequently, it effectively accelerates drones‘ usages at personal and governmental levels.

Keywords: detection, drone, jamming, prevention, privacy, RF, radar, UAV

Procedia PDF Downloads 197

Authors: E. Karakulak, R. Yamanoğlu, M. Zeren

Abstract:

In the current study, fly ash obtained from a thermal power plant was used as reinforcement in pure magnesium. The composite materials with different fly ash contents were produced with powder metallurgical methods. Powder mixtures were sintered at 540^oC under 30 MPa pressure for 15 minutes in a vacuum assisted hot press. Results showed that increasing ash content continuously increases hardness of the composite. On the other hand, minimum wear damage was obtained at 2 wt. % ash content. Addition of higher level of fly ash results with formation of cracks in the matrix and increases wear damage of the material.

Keywords: Mg composite, fly ash, wear, powder metallurgy

Procedia PDF Downloads 355

Authors: Thanakrit Taweesoontorn, Sarucha Yanyong, Poom Konghuayrob

Abstract:

Robotic arms have gained popularity in various industries due to their accuracy and efficiency. This research proposes a method for bin-picking tasks using the Cobot, combining the YOLOv5 CNNs model for object detection and pose estimation with traditional feature detection (FAST), feature description (BRISK), and matching algorithms. By integrating these algorithms and utilizing a small-scale depth sensor camera for capturing depth and color images, the system achieves real-time object detection and accurate pose estimation, enabling the robotic arm to pick objects correctly in both position and orientation. Furthermore, the proposed method is implemented within the ROS framework to provide a seamless platform for robotic control and integration. This integration of robotics, cameras, and AI technology contributes to the development of industrial robotics, opening up new possibilities for automating challenging tasks and improving overall operational efficiency.

Keywords: robotic vision, image processing, applications of robotics, artificial intelligent

Procedia PDF Downloads 76