Search results for: localized surface plasmon resonance detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10281

Search results for: localized surface plasmon resonance detection

9471 Temperature and Substrate Orientation Effects on the Thermal Stability of Graphene Sheet Attached on the Si Surface

Authors: Wen-Jay Lee, Kuo-Ning Chiang

Abstract:

The graphene binding with silicon substrate has apparently Schottky barriers property, which can be used in the application of solar cell and light source. Because graphene has only one atom layer, the atomistic structure of graphene binding with the silicon surface plays an important role to affect the properties of graphene. In this work, temperature effect on the morphology of graphene sheet attached on different crystal planes of silicon substrates are investigated by Molecular dynamics (MD) (LAMMPS, developed by Sandia National Laboratories). The results show that the covered graphene sheet would cause the structural deformation of the surface Si atoms of stubtrate. To achieve a stable state in the binding process, the surface Si atoms would adjust their position and fit the honeycomb structure of graphene after the graphene attaches to the Si surface. The height contour of graphene on different plane of silicon surfaces presents different pattern, leading the local residual stress at the interface. Due to the high density of dangling bond on the Si (111)7x7 surface, the surface of Si(111)7x7 is not matching with the graphene so well in contrast with Si(100)2x1and Si(111)2x1. Si(111)7x7 is found that only partial silicon adatoms are rearranged on surface after the attachment when the temperature is lower than 200K, As the temperature gradually increases, the deformation of surface structure becomes significant, as well as the residue stress. With increasing temperature till the 815K, the graphene sheet begins to destroy and mixes with the silicon atoms. For the Si(100)2x1 and Si(111)2x1, the silicon surface structure keep its structural arrangement with a higher temperature. With increasing temperature, the residual stress gradually decrease till a critical temperatures. When the temperature is higher than the critical temperature, the residual stress gradually increases and the structural deformation is found on the surface of the Si substrates.

Keywords: molecular dynamics, graphene, silicon, Schottky barriers, interface

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9470 Sequential Data Assimilation with High-Frequency (HF) Radar Surface Current

Authors: Lei Ren, Michael Hartnett, Stephen Nash

Abstract:

The abundant measured surface current from HF radar system in coastal area is assimilated into model to improve the modeling forecasting ability. A simple sequential data assimilation scheme, Direct Insertion (DI), is applied to update model forecast states. The influence of Direct Insertion data assimilation over time is analyzed at one reference point. Vector maps of surface current from models are compared with HF radar measurements. Root-Mean-Squared-Error (RMSE) between modeling results and HF radar measurements is calculated during the last four days with no data assimilation.

Keywords: data assimilation, CODAR, HF radar, surface current, direct insertion

Procedia PDF Downloads 560
9469 Synthesis of Fullerene Nanorods for Detection of Ethylparaben an Endocrine Disruptor in Cosmetics

Authors: Jahangir Ahmad Rather, Emad A. Khudaish, Ahsanulhaq Qurashi, Palanisamy Kannan

Abstract:

Chemical modification and assembling of fullerenes are fundamentally important for the application of fullerenes as functional molecules and in molecular devices and organic electronic devices. We have synthesized fullerene nanorods C60NRs conjugate via liquid-liquid interface and the synthesized C60NRs was characterized by FTIR spectroscopy, field emission electron microscopy (FESEM) and X-ray diffraction techniques. The C60NRs were immobilized on glassy carbon electrode via surface bound diazonium salts as an impact strategy. This method involves electrografting of p–nitrophenyl to give GCE–Ph–NO2 and then the terminal nitro-group was chemically reduced to GCE–Ph–NH2 in a presence of sodium borohydride/gold–polyaniline nanocomposite (NaBH4/Au–PANI). The Au–PANI composite was synthesized and characterized by FTIR, UV-vis, SEM and EDX techniques. The C60NRs were immobilized on GCE–Ph–NH2 via amination reaction which involves N-H addition across a π-bond on [60] fullerene. The immobilized C60NRs/GCE was subjected to electrochemical reduction in 1.0 M KOH to yield ERC60NRs/GCE sensor. The developed sensor shows high electrocatalytic activity for the detection of ethylparaben (EP) over a concentration range from 0.01 to 0.52 µM with a detection limit (LOD) 3.8 nM. The amount of EP present in the nourishing repair cream (OlAY®) was determined by standard addition method at the developed ERC60NRs/GCE sensor. The total concentration of EP was found to be 0.011 µM (0.1%) and is within the permissible limit of 0.19 % EP in cosmetics according to the European scientific committee (SCCS) on consumer safety on 22 March 2011 (SCCS/1348/11).

Keywords: diazonium salt reduction, ethylparaben (EP), endocrine disruptor, fullerene nanorods (C60NRs), gold–polyaniline nanocomposite (Au–PANI)

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9468 Vibratinal Spectroscopic Identification of Beta-Carotene in Usnic Acid and PAHs as a Potential Martian Analogue

Authors: A. I. Alajtal, H. G. M. Edwards, M. A. Elbagermi

Abstract:

Raman spectroscopy is currently a part of the instrumentation suite of the ESA ExoMars mission for the remote detection of life signatures in the Martian surface and subsurface. Terrestrial analogues of Martian sites have been identified and the biogeological modifications incurred as a result of extremophilic activity have been studied. Analytical instrumentation protocols for the unequivocal detection of biomarkers in suitable geological matrices are critical for future unmanned explorations, including the forthcoming ESA ExoMars mission to search for life on Mars scheduled for 2018 and Raman spectroscopy is currently a part of the Pasteur instrumentation suite of this mission. Here, Raman spectroscopy using 785nm excitation was evaluated for determining various concentrations of beta-carotene in admixture with polyaromatic hydrocarbons and usnic acid have been investigated by Raman microspectrometry to determine the lowest levels detectable in simulation of their potential identification remotely in geobiological conditions in Martian scenarios. Information from this study will be important for the development of a miniaturized Raman instrument for targetting Martian sites where the biosignatures of relict or extant life could remain in the geological record.

Keywords: raman spectroscopy, mars-analog, beta-carotene, PAHs

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9467 Accumulation of Phlorotannins in Abalone Haliotis discus Hannai after Feeding with Eisenia bicyclis

Authors: Bangoura Issa, Ji-Young Kang, M. T. H. Chowdhury, Ji-Eun Lee, Yong-Ki Hong

Abstract:

Investigation was carried out for the production of value-added abalone Haliotis discus hannai containing bioactive phlorotannin by feeding phlorotannin-rich seaweed Eisenia bicyclis 2 weeks prior to harvesting. Accumulation of phlorotannins was proceded by feeding with E. bicyclis after 4 days of starvation. HPLC purification afforded two major phlorotannins. Mass spectrometry and 1H-nuclear magnetic resonance analysis clarified their structures to be as 7-phloroeckol and eckol. Throughout the feeding period of 20 days, 7-phloroeckolol was accumulated in the muscle (foot muscle tissue) up to 0.18±0.12 mg g-1 dry weight of tissue after 12 days. Eckol reached 0.21±0.03 mg g-1 dry weight of tissue after 18 days. By feeding Laminaria japonica as reference, abalone showed no detection of phlorotannins in the muscle tissue. Seaweed consumption and growth rate of abalone revealed almost similar when feed with E. bicyclis or L. japonicain 20 days. Phlorotannins reduction to half-maximal accumulation values took 1.0 day and 2.7 days for 7-phloroeckol and eckol respectively, after replacing the feed to L. japonica.

Keywords: abalone, accumulation, eisenia bicyclis, phlorotannins

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9466 CFD Study of Free Surface Flows Resulting from a Dam-Breaking

Authors: Sonia Ben Hamza, Sabra Habli, Nejla Mahjoub Saïd, Hervé Bournot, Georges Le Palec

Abstract:

Free surface flows caused by dam breaks in channels or rivers is an attention-getting subject to the engineering practice, however, the studies are few to be reported. In this paper, a numerical investigation of unsteady free surface flows resulting from a dam-breaking in a rectangular channel is studied. Numerical computations were carried out using ANSYS Fluent which is based on the finite volume approach. The air/water interface was modeled with the volume of fluid method (VOF). Verification for a typical dam-break problem is analyzed by comparing the present results with others and very good agreement is obtained. The present approach is then used to predict the characteristics of free surface flow due to the dam breaking in channel. The characteristics of complex unsteady free surface flow in these examples are clearly explained. The numerical results show that the flow became more disturbed after impacting the vertical wall, then a recirculation zone, as well as turbulence phenomena, were created. At this instant, a cavity of air was included on the flow. The results agree well with the experimental data found in the literature.

Keywords: CFD, dam-break, free surface, turbulent flows, VOF

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9465 Enhanced Near-Infrared Upconversion Emission Based Lateral Flow Immunoassay for Background-Free Detection of Avian Influenza Viruses

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

Abstract:

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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9464 Based on MR Spectroscopy, Metabolite Ratio Analysis of MRI Images for Metastatic Lesion

Authors: Hossain A, Hossain S.

Abstract:

Introduction: In a small cohort, we sought to assess the magnetic resonance spectroscopy's (MRS) ability to predict the presence of metastatic lesions. Method: A Popular Diagnostic Centre Limited enrolled patients with neuroepithelial tumors. The 1H CSI MRS of the brain allows us to detect changes in the concentration of specific metabolites caused by metastatic lesions. Among these metabolites are N-acetyl-aspartate (NNA), creatine (Cr), and choline (Cho). For Cho, NAA, Cr, and Cr₂, the metabolic ratio was calculated using the division method. Results: The NAA values were 0.63 and 5.65 for tumor cells, 1.86 and 5.66 for normal cells, and 1.86 and 5.66 for normal cells 2. NAA values for normal cells 1 were 1.84, 10.6, and 1.86 for normal cells 2, respectively. Cho levels were as low as 0.8 and 10.53 in the tumor cell, compared to 1.12 and 2.7 in the normal cell 1 and 1.24 and 6.36 in the normal cell 2. Cho/Cr₂ barely distinguished itself from the other ratios in terms of significance. For tumor cells, the ratios of Cho/NAA, Cho/Cr₂, NAA/Cho, and NAA/Cr₂ were significant. Normal cell 1 had significant Cho/NAA, Cho/Cr, NAA/Cho, and NAA/Cr ratios. Conclusion: The clinical result can be improved by using 1H-MRSI to guide the size of resection for metastatic lesions. Even though it is non-invasive and doesn't present any difficulties during the procedure, MRS has been shown to predict the detection of metastatic lesions.

Keywords: metabolite ratio, MRI images, metastatic lesion, MR spectroscopy, N-acetyl-aspartate

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9463 An Investigation into Fraud Detection in Financial Reporting Using Sugeno Fuzzy Classification

Authors: Mohammad Sarchami, Mohsen Zeinalkhani

Abstract:

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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9462 Memory and Narratives Rereading before and after One Week

Authors: Abigail M. Csik, Gabriel A. Radvansky

Abstract:

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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9461 The Qualitative and Quantitative Detection of Pistachio in Processed Food Products Using Florescence Dye Based PCR

Authors: Ergün Şakalar, Şeyma Özçirak Ergün

Abstract:

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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9460 Experimental Research of Corrosion Resistance Desalination Plant Pipe According to Weld Overlay Layers

Authors: Ryu Wonjin, Choi Hyeok, Park Joonhong

Abstract:

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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9459 Study of Bolt Inclination in a Composite Single Bolted Joint

Authors: Faci Youcef, Ahmed Mebtouche, Djillali Allou, Maalem Badredine

Abstract:

The inclination of the bolt in a fastened joint of composite material during a tensile test can be influenced by several parameters, including material properties, bolt diameter and length, the type of composite material being used, the size and dimensions of the bolt, bolt preload, surface preparation, the design and configuration of the joint, and finally testing conditions. These parameters should be carefully considered and controlled to ensure accurate and reliable results during tensile testing of composite materials with fastened joints. Our work focuses on the effect of the stacking sequence and the geometry of specimens. An experimental test is carried out to obtain the inclination of a bolt during a tensile test of a composite material using acoustic emission and digital image correlation. Several types of damage were obtained during the load. Digital image correlation techniques permit the obtaining of the inclination of bolt angle value during tensile test. We concluded that the inclination of the bolt during a tensile test of a composite material can be related to the damage that occurs in the material. It can cause stress concentrations and localized deformation in the material, leading to damage such as delamination, fiber breakage, matrix cracking, and other forms of failure.

Keywords: damage, inclination, analyzed, carbon

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9458 Detailed Investigation of Thermal Degradation Mechanism and Product Characterization of Co-Pyrolysis of Indian Oil Shale with Rubber Seed Shell

Authors: Bhargav Baruah, Ali Shemsedin Reshad, Pankaj Tiwari

Abstract:

This work presents a detailed study on the thermal degradation kinetics of co-pyrolysis of oil shale of Upper Assam, India with rubber seed shell, and lab-scale pyrolysis to investigate the influence of pyrolysis parameters on product yield and composition of products. The physicochemical characteristics of oil shale and rubber seed shell were studied by proximate analysis, elemental analysis, Fourier transform infrared spectroscopy and X-ray diffraction. The physicochemical study showed the mixture to be of low moisture, high ash, siliceous, sour with the presence of aliphatic, aromatic, and phenolic compounds. The thermal decomposition of the oil shale with rubber seed shell was studied using thermogravimetric analysis at heating rates of 5, 10, 20, 30, and 50 °C/min. The kinetic study of the oil shale pyrolysis process was performed on the thermogravimetric (TGA) data using three model-free isoconversional methods viz. Friedman, Flynn Wall Ozawa (FWO), and Kissinger Akahira Sunnose (KAS). The reaction mechanisms were determined using the Criado master plot. The understanding of the composition of Indian oil shale and rubber seed shell and pyrolysis process kinetics can help to establish the experimental parameters for the extraction of valuable products from the mixture. Response surface methodology (RSM) was employed usinf central composite design (CCD) model to setup the lab-scale experiment using TGA data, and optimization of process parameters viz. heating rate, temperature, and particle size. The samples were pre-dried at 115°C for 24 hours prior to pyrolysis. The pyrolysis temperatures were set from 450 to 650 °C, at heating rates of 2 to 20°C/min. The retention time was set between 2 to 8 hours. The optimum oil yield was observed at 5°C/min and 550°C with a retention time of 5 hours. The pyrolytic oil and gas obtained at optimum conditions were subjected to characterization using Fourier transform infrared spectroscopy (FT-IR) gas chromatography and mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR).

Keywords: Indian oil shale, rubber seed shell, co-pyrolysis, isoconversional methods, gas chromatography, nuclear magnetic resonance, Fourier transform infrared spectroscopy

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9457 Independent Control over Surface Charge and Wettability Using Polyelectrolyte Architecture

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

Abstract:

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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9456 Speech Detection Model Based on DNN Classifier for Speech Emotions Recognition

Authors: Aisultan Shoiynbek, Darkhan Kuanyshbay, Paulo Menezes, Akbayan Bekarystankyzy, Assylbek Mukhametzhanov, Temirlan Shoiynbek

Abstract:

Speech emotion recognition has received increasing research interest in recent years. Most research has utilized emotional speech collected under controlled conditions, which was recorded by actors imitating and artificially producing emotions in front of a microphone. There are four issues related to that approach: (1) emotions are not natural, meaning that machines are learning to recognize fake emotions; (2) emotions are very limited in quantity and poor in variety of speaking; (3) there is some language dependency in SER; (4) consequently, each time researchers want to start work with SER, they need to find a good emotional database in their language. This paper proposes an approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describes the sequence of actions involved in the proposed approach. One of the first objectives in the sequence of actions is the speech detection issue. The paper provides a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To investigate the working capacity of the developed model, an analysis of speech detection and extraction from real tasks has been performed.

Keywords: deep neural networks (DNN), speech detection, speech emotion recognition (SER), Mel-frequency cepstrum coefficients (MFCC), collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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9455 Frequency Modulation Continuous Wave Radar Human Fall Detection Based on Time-Varying Range-Doppler Features

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

Abstract:

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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9454 Characterization and Detection of Cadmium Ion Using Modification Calixarene with Multiwalled Carbon Nanotubes

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

Abstract:

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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9453 Chinese Event Detection Technique Based on Dependency Parsing and Rule Matching

Authors: Weitao Lin

Abstract:

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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9452 Robust Barcode Detection with Synthetic-to-Real Data Augmentation

Authors: Xiaoyan Dai, Hsieh Yisan

Abstract:

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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9451 Pelvic Floor Electrophysiology Patterns Associated with Obstructed Defecation

Authors: Emmanuel Kamal Aziz Saba, Gihan Abd El-Lateif Younis El-Tantawi, Mohammed Hamdy Zahran, Ibrahim Khalil Ibrahim, Mohammed Abd El-Salam Shehata, Hussein Al-Moghazy Sultan, Medhat

Abstract:

Pelvic floor electrophysiological tests are essential for assessment of patients with obstructed defecation. The present study was conducted to determine the different patterns of pelvic floor electrophysiology that are associated with obstructed defecation. The present cross sectional study included 25 patients with obstructed defecation. A control group of 20 apparently healthy subjects were included. All patients were subjected to history taking, clinical examination, proctosigmoidoscopy, lateral proctography (evacuation proctography), dynamic pelvic magnetic resonance imaging, anal manometry and electrophysiological studies. Electrophysiological studies were including pudendal nerve motor conduction study, pudendo-anal reflex, needle electromyography of external anal sphincter and puborectalis muscles, pudendal somatosensory evoked potential and tibial somatosensory evoked potential. The control group was subjected to electrophysiological studies which included pudendal nerve motor conduction study, pudendo-anal reflex, pudendal somatosensory evoked potential and tibial somatosensory evoked potential. The most common pelvic floor electrodiagnostic pattern characteristics of obstructed defecation was pudendal neuropathy, denervation and anismus of external anal sphincter and puborectalis with complete interference pattern of external anal sphincter and puborectalis at squeezing and cough and no localized defect in external anal sphincter. In conclusion, there were characteristic pelvic floor electrodiagnostic patterns associated with obstructed defecation.

Keywords: obstructed defecation, pudendal nerve terminal motor latency, pudendoanal reflex, sphincter electromyography

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9450 A Fast Silhouette Detection Algorithm for Shadow Volumes in Augmented Reality

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

Abstract:

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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9449 Capturing the Stress States in Video Conferences by Photoplethysmographic Pulse Detection

Authors: Jarek Krajewski, David Daxberger

Abstract:

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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9448 Dam Break Model Using Navier-Stokes Equation

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

Abstract:

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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9447 Surface Flattening Assisted with 3D Mannequin Based on Minimum Energy

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

Abstract:

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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9446 Electrical Equivalent Analysis of Micro Cantilever Beams for Sensing Applications

Authors: B. G. Sheeparamatti, J. S. Kadadevarmath

Abstract:

Microcantilevers are the basic MEMS devices, which can be used as sensors, actuators, and electronics can be easily built into them. The detection principle of microcantilever sensors is based on the measurement of change in cantilever deflection or change in its resonance frequency. The objective of this work is to explore the analogies between the mechanical and electrical equivalent of microcantilever beams. Normally scientists and engineers working in MEMS use expensive software like CoventorWare, IntelliSuite, ANSYS/Multiphysics, etc. This paper indicates the need of developing the electrical equivalent of the MEMS structure and with that, one can have a better insight on important parameters, and their interrelation of the MEMS structure. In this work, considering the mechanical model of the microcantilever, the equivalent electrical circuit is drawn and using a force-voltage analogy, it is analyzed with circuit simulation software. By doing so, one can gain access to a powerful set of intellectual tools that have been developed for understanding electrical circuits. Later the analysis is performed using ANSYS/Multiphysics - software based on finite element method (FEM). It is observed that both mechanical and electrical domain results for a rectangular microcantilevers are in agreement with each other.

Keywords: electrical equivalent circuit analogy, FEM analysis, micro cantilevers, micro sensors

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9445 Study on Robot Trajectory Planning by Robot End-Effector Using Dual Curvature Theory of the Ruled Surface

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

Abstract:

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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9444 The Wear Recognition on Guide Surface Based on the Feature of Radar Graph

Authors: Youhang Zhou, Weimin Zeng, Qi Xie

Abstract:

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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9443 Bundle Block Detection Using Spectral Coherence and Levenberg Marquardt Neural Network

Authors: K. Padmavathi, K. Sri Ramakrishna

Abstract:

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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9442 Influence of Selected Finishing Technologies on the Roughness Parameters of Stainless Steel Manufactured by Selective Laser Melting Method

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

Abstract:

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

Procedia PDF Downloads 123