Search results for: face presentation attack detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7559

Search results for: face presentation attack detection

5639 Electrochemiluminescent Detection of DNA Damage Induced by Tetrachloro-1,4- Benzoquinone Using DNA Sensor

Authors: Tian-Fang Kang, Xue Sun

Abstract:

DNA damage induced by tetrachloro-1,4-benzoquinone (TCBQ), a reactive metabolite of pentachloro-phenol (PCP), was investigated using a glassy carbon electrode (GCE) modified with calf thymus double-stranded DNA (ds-DNA) in this work. DNA modified films were constructed by layer-by-layer adsorption of polycationic poly(diallyldimethyl- ammonium chloride) (PDDA) and negatively charged ds-DNA on the surface of a glassy carbon electrode. The DNA intercalator [Ru(bpy)2(dppz)]2+ (bpy=2, 2′-bipyridine, dppz0dipyrido [3, 2-a: 2′,3′-c] phenazine) was chosen as an electrochemical probe to detect DNA damage. After the sensor was incubated in 0.1 M pH 7.3 phosphate buffer solution (PBS) for 30min, the intact PDDA/DNA film produced a sensitive electrochemiluminescent (ECL) signal. However, after the sensor was incubated in 100 μM TCBQ or a mixed solution of 100 μM TCBQ and 2 mM H2O2, ECL signal decreased significantly. During the incubation of DNA in TCBQ or TCBQ-H2O2 solution, the double-helix of DNA was damaged, which resulted in the decrease of Ru-dppz bound to DNA. Additionally, the results were verified independently by fluorescence experiments. This paper provides a sensitive method to directly screen DNA damage induced by chemicals in the environment.

Keywords: DNA damage, detection, electrochemiluminescence, sensor

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5638 Directional Search for Dark Matter Using Nuclear Emulsion

Authors: Ali Murat Guler

Abstract:

A variety of experiments have been developed over the past decades, aiming at the detection of Weakly Interactive Massive Particles (WIMPs) via their scattering in an instrumented medium. The sensitivity of these experiments has improved with a tremendous speed, thanks to a constant development of detectors and analysis methods. Detectors capable of reconstructing the direction of the nuclear recoil induced by the WIMP scattering are opening a new frontier to possibly extend Dark Matter searches beyond the neutrino background. Measurement of WIMP’s direction will allow us to detect the galactic origin of dark matter and, therefore to have a clear signal-background separation. The NEWSdm experiment, based on nuclear emulsions, is intended to measure the direction of WIMP-induced nuclear coils with a solid-state detector, thus with high sensitivity. We discuss the discovery potential of a directional experiment based on the use of a solid target made of newly developed nuclear emulsions and novel read-out systems achieving nanometric resolution. We also report results of a technical test conducted in Gran Sasso.

Keywords: dark matter, direct detection, nuclear emulsion, WIMPS

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5637 Computer Aided Diagnostic System for Detection and Classification of a Brain Tumor through MRI Using Level Set Based Segmentation Technique and ANN Classifier

Authors: Atanu K Samanta, Asim Ali Khan

Abstract:

Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: brain tumor, computer-aided diagnostic (CAD) system, gray-level co-occurrence matrix (GLCM), tumor segmentation, level set method

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5636 Cut-Off of CMV Cobas® Taqman® (CAP/CTM Roche®) for Introduction of Ganciclovir Pre-Emptive Therapy in Allogeneic Hematopoietic Stem Cell Transplant Recipients

Authors: B. B. S. Pereira, M. O. Souza, L. P. Zanetti, L. C. S. Oliveira, J. R. P. Moreno, M. P. Souza, V. R. Colturato, C. M. Machado

Abstract:

Background: The introduction of prophylactic or preemptive therapies has effectively decreased the CMV mortality rates after hematopoietic stem cell transplantation (HSCT). CMV antigenemia (pp65) or quantitative PCR are methods currently approved for CMV surveillance in pre-emptive strategies. Commercial assays are preferred as cut-off levels defined by in-house assays may vary among different protocols and in general show low reproducibility. Moreover, comparison of published data among different centers is only possible if international standards of quantification are included in the assays. Recently, the World Health Organization (WHO) established the first international standard for CMV detection. The real time PCR COBAS Ampliprep/ CobasTaqMan (CAP/CTM) (Roche®) was developed using the WHO standard for CMV quantification. However, the cut-off for the introduction of antiviral has not been determined yet. Methods: We conducted a retrospective study to determine: 1) the sensitivity and specificity of the new CMV CAP/CTM test in comparison with pp65 antigenemia to detect episodes of CMV infection/reactivation, and 2) the cut-off of viral load for introduction of ganciclovir (GCV). Pp65 antigenemia was performed and the corresponding plasma samples were stored at -20°C for further CMV detection by CAP/CTM. Comparison of tests was performed by kappa index. The appearance of positive antigenemia was considered the state variable to determine the cut-off of CMV viral load by ROC curve. Statistical analysis was performed using SPSS software version 19 (SPSS, Chicago, IL, USA.). Results: Thirty-eight patients were included and followed from August 2014 through May 2015. The antigenemia test detected 53 episodes of CMV infection in 34 patients (89.5%), while CAP/CTM detected 37 episodes in 33 patients (86.8%). AG and PCR results were compared in 431 samples and Kappa index was 30.9%. The median time for first AG detection was 42 (28-140) days, while CAP/CTM detected at a median of 7 days earlier (34 days, ranging from 7 to 110 days). The optimum cut-off value of CMV DNA was 34.25 IU/mL to detect positive antigenemia with 88.2% of sensibility, 100% of specificity and AUC of 0.91. This cut-off value is below the limit of detection and quantification of the equipment which is 56 IU/mL. According to CMV recurrence definition, 16 episodes of CMV recurrence were detected by antigenemia (47.1%) and 4 (12.1%) by CAP/CTM. The duration of viremia as detected by antigenemia was shorter (60.5% of the episodes lasted ≤ 7 days) in comparison to CAP/CTM (57.9% of the episodes lasting 15 days or more). This data suggests that the use of antigenemia to define the duration of GCV therapy might prompt early interruption of antiviral, which may favor CMV reactivation. The CAP/CTM PCR could possibly provide a safer information concerning the duration of GCV therapy. As prolonged treatment may increase the risk of toxicity, this hypothesis should be confirmed in prospective trials. Conclusions: Even though CAP/CTM by ROCHE showed great qualitative correlation with the antigenemia technique, the fully automated CAP/CTM did not demonstrate increased sensitivity. The cut-off value below the limit of detection and quantification may result in delayed introduction of pre-emptive therapy.

Keywords: antigenemia, CMV COBAS/TAQMAN, cytomegalovirus, antiviral cut-off

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5635 Canadian Business Leaders’ Phenomenological Online Education Expansion

Authors: Amna Khaliq

Abstract:

This research project centers on Canadian business leaders’ phenomenological online education expansion by navigating the challenges faced by strategic leaders concerning the expansion of online education in the Canadian higher education sector from a business perspective. The study identifies the problems and opportunities of faculty members’ transition from traditional face-to-face to online instruction, particularly in the context of technology-enhanced learning (TEL), and their influence on the growth strategies of Canadian educational institutions. It explores strategic leaders’ approaches and the impact of emerging technologies to assist with developing and executing business strategies to expand online education in Canada. As online education has gained prominence in the country, this research addresses a relevant business problem for educational institutions. The research employs a phenomenological approach in the qualitative research design to conduct this investigation. The study interviews eighteen faculty members engaged in online education in Canada. The interview data is analyzed to answer the three research questions for strategic leaders to expand online education with higher education institutions in Canada. The recommendations include 1) data privacy, infrastructure, security, and technology, 2) support and training for student engagement, 3) accessibility and inclusion, and 4) collaboration among institutions associated with expanding online education.

Keywords: strategic leadership, Canada, education, technology

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5634 Motivation in Online Instruction

Authors: David Whitehouse

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Some of the strengths of online teaching include flexibility, creativity, and comprehensiveness. A challenge can be motivation. How can an instructor repeating the same lessons over and over, day in and day out, year after year, maintain motivation? Enthusiasm? Does motivating the student and creating enthusiasm in class build the same things inside the instructor? The answers lie in the adoption of what I label EUQ—The Empathy and Understanding Quotient. In the online environment, students who are adults have many demands on their time: civilian careers, families (spouse, children, older parents), and sometimes even military service. Empathetic responses on the part of the instructor will lead to open and honest communication on the part of the student, which will lead to understanding on the part of the instructor and a rise in motivation in both parties. Understanding the demands can inform an instructor’s relationship with the student throughout the temporal parameters of classwork. In practicing EUQ, instructors can build motivation in their students and find internal motivation in an enhanced classroom dynamic. The presentation will look at what motivates a student to accomplish more than the minimum required and how that can lead to excellent results for an instructor’s own motivation. Through direct experience of having students give high marks on post-class surveys and via direct messaging, the presentation will focus on how applying EUQ in granting extra time, searching for intent while grading, communicating with students via Quick Notes, responses in Forums, comments in Assignments, and comments in grading areas - - - how applying these things infuses enthusiasm and energy in the instructor which drive creativity in teaching. Three primary ways of communicating with students will be given as examples. The positive response and negative response each for a Forum, an Assignment, and a Message will be explored. If there is time, participants will be invited to craft their own EUQ responses in a role playing exercise involving two common classroom scenarios—late work and plagiarism.

Keywords: education, instruction, motivation, online, teaching

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5633 Volatile Organic Compounds Detection by Surface Acoustic Wave Sensors with Nanoparticles Embedded in Polymer Sensitive Layers

Authors: Cristian Viespe, Dana Miu

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Surface acoustic wave (SAW) sensors with nanoparticles (NPs) of various dimensions and concentrations embedded in different types of polymer sensing films for detecting volatile organic compounds (VOCs) were studied. The sensors were ‘delay line’ type with a center frequency of 69.4 MHz on ST-X quartz substrates. NPs with different diameters of 7 nm or 13 nm were obtained by laser ablation with lasers having 5 ns or 10 ps pulse durations, respectively. The influence of NPs dimensions and concentrations on sensor properties such as frequency shift, sensitivity, noise and response time were investigated. To the best of our knowledge, the influence of NP dimensions on SAW sensor properties with has not been investigated. The frequency shift and sensitivity increased with increasing NP concentration in the polymer for a given NP dimension and with decreasing NP diameter for a given concentration. The best performances were obtained for the smallest NPs used. The SAW sensor with NPs of 7 nm had a limit of detection (LOD) of 65 ppm (almost five times better than the sensor with polymer alone), and a response time of about 9 s for ethanol.

Keywords: surface acoustic wave sensor, nanoparticles, volatile organic compounds, laser ablation

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5632 Temperature-Based Detection of Initial Yielding Point in Loading of Tensile Specimens Made of Structural Steel

Authors: Aqsa Jamil, Tamura Hiroshi, Katsuchi Hiroshi, Wang Jiaqi

Abstract:

The yield point represents the upper limit of forces which can be applied to a specimen without causing any permanent deformation. After yielding, the behavior of the specimen suddenly changes, including the possibility of cracking or buckling. So, the accumulation of damage or type of fracture changes depending on this condition. As it is difficult to accurately detect yield points of the several stress concentration points in structural steel specimens, an effort has been made in this research work to develop a convenient technique using thermography (temperature-based detection) during tensile tests for the precise detection of yield point initiation. To verify the applicability of thermography camera, tests were conducted under different loading conditions and measuring the deformation by installing various strain gauges and monitoring the surface temperature with the help of a thermography camera. The yield point of specimens was estimated with the help of temperature dip, which occurs due to the thermoelastic effect during the plastic deformation. The scattering of the data has been checked by performing a repeatability analysis. The effects of temperature imperfection and light source have been checked by carrying out the tests at daytime as well as midnight and by calculating the signal to noise ratio (SNR) of the noised data from the infrared thermography camera, it can be concluded that the camera is independent of testing time and the presence of a visible light source. Furthermore, a fully coupled thermal-stress analysis has been performed by using Abaqus/Standard exact implementation technique to validate the temperature profiles obtained from the thermography camera and to check the feasibility of numerical simulation for the prediction of results extracted with the help of the thermographic technique.

Keywords: signal to noise ratio, thermoelastic effect, thermography, yield point

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5631 A Novel Study Contrasting Traditional Autopsy with Post-Mortem Computed Tomography in Falls Leading to Death

Authors: Balaji Devanathan, Gokul G., Abilash S., Abhishek Yadav, Sudhir K. Gupta

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Background: As an alternative to the traditional autopsy, a virtual autopsy is carried out using scanning and imaging technologies, mainly post-mortem computed tomography (PMCT). This facility aims to supplement traditional autopsy results and reduce or eliminate internal dissection in subsequent autopsies. For emotional and religious reasons, the deceased's relatives have historically disapproved such interior dissection. The non-invasive, objective, and preservative PMCT is what friends and family would rather have than a traditional autopsy. Additionally, it aids in the examination of the technologies and the benefits and drawbacks of each, demonstrating the significance of contemporary imaging in the field of forensic medicine. Results: One hundred falls resulting in fatalities was analysed by the writers. Before the autopsy, each case underwent a PMCT examination using a 16-slice Multi-Slice CT spiral scanner. By using specialised software, MPR and VR reconstructions were carried out following the capture of the raw images. The accurate detection of fractures in the skull, face bones, clavicle, scapula, and vertebra was better observed in comparison to a routine autopsy. The interpretation of pneumothorax, Pneumoperitoneum, pneumocephalus, and hemosiuns are much enhanced by PMCT than traditional autopsy. Conclusion. It is useful to visualise the skeletal damage in fall from height cases using a virtual autopsy based on PMCT. So, the ideal tool in traumatising patients is a virtual autopsy based on PMCT scans. When assessing trauma victims, PMCT should be viewed as an additional helpful tool to traditional autopsy. This is because it can identify additional bone fractures in body parts that are challenging to examine during autopsy, such as posterior regions, which helps the pathologist reconstruct the victim's life and determine the cause of death.

Keywords: PMCT, fall from height, autopsy, fracture

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5630 The Influence of Project-Based Learning and Outcome-Based Education: Interior Design Tertiary Students in Focus

Authors: Omneya Messallam

Abstract:

Technology has been developed dramatically in most of the educational disciplines. For instance, digital rendering subject, which is being taught in both Interior and Architecture fields, is witnessing almost annually updated software versions. A lot of students and educators argued that there will be no need for manual rendering techniques to be learned. Therefore, the Interior Design Visual Presentation 1 course (ID133) has been chosen from the first level of the Interior Design (ID) undergraduate program, as it has been taught for six years continually. This time frame will facilitate sound observation and critical analysis of the use of appropriate teaching methodologies. Furthermore, the researcher believes in the high value of the manual rendering techniques. The course objectives are: to define the basic visual rendering principles, to recall theories and uses of various types of colours and hatches, to raise the learners’ awareness of the value of studying manual render techniques, and to prepare them to present their work professionally. The students are female Arab learners aged between 17 and 20. At the outset of the course, the majority of them demonstrated negative attitude, lacking both motivation and confidence in manual rendering skills. This paper is a reflective appraisal of deploying two student-centred teaching pedagogies which are: Project-based learning (PBL) and Outcome-based education (OBE) on ID133 students. This research aims of developing some teaching strategies to enhance the quality of teaching in this given course over an academic semester. The outcome of this research emphasized the positive influence of applying such educational methods on improving the quality of students’ manual rendering skills in terms of: materials, textiles, textures, lighting, and shade and shadow. Furthermore, it greatly motivated the students and raised the awareness of the importance of learning the manual rendering techniques.

Keywords: project-based learning, outcome-based education, visual presentation, manual render, personal competences

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5629 Malaysia as a Case Study for Climate Policy Integration into Energy Policy

Authors: Marcus Lee

Abstract:

The energy sector is the largest contributor of greenhouse gas emissions in Malaysia, which induces climate change. The climate change problem is therefore an energy sector problem. Tackling climate change issues successfully is contingent on actions taken in the energy sector. The researcher propounds that ‘Climate Policy Integration’ (CPI) into energy policy is a viable and insufficiently developed strategy in Malaysia that promotes the synergies between climate change and energy objectives, in order to achieve the targets found in both climate change and energy policies. In exploring this hypothesis, this paper presentation will focus on two particular aspects. Firstly, the meaning of CPI as an approach and as a concept will be explored. As an approach, CPI into energy policy means the integration of climate change objectives into the energy policy area. Its subject matter focuses on establishing the functional interrelations between climate change and energy objectives, by promoting their synergies and minimising their contradictions. However, its conceptual underpinnings are less than straightforward. Drawing from the ‘principle of integration’ found in international treaties and declarations such as the Stockholm Declaration 1972, the Rio Declaration 1992 and the United Nations Framework on Climate Change 1992 (‘UNFCCC’), this paper presentation will explore the contradictions in international standards on how the sustainable development tenets of environmental sustainability, social development and economic development are to be balanced and its relevance to CPI. Further, the researcher will consider whether authority may be derived from international treaties and declarations in order to argue for the prioritisation of environmental sustainability over the other sustainable development tenets through CPI. Secondly, this paper presentation will also explore the degree to which CPI into energy policy has been achieved and pursued in Malaysia. In particular, the strength of the conceptual framework with regard to CPI in Malaysian governance will be considered by assessing Malaysia’s National Policy on Climate Change (2009) (‘NPCC 2009’). The development (or the lack of) of CPI as an approach since the publication of the NPCC 2009 will also be assessed based on official government documents and policies that may have a climate change and/or energy agenda. Malaysia’s National Renewable Energy Policy and Action Plan (2010), draft National Energy Efficiency Action Plan (2014), Intended Nationally Determined Contributions (2015) in relation to the Paris Agreement, 11th Malaysia Plan (2015) and Biennial Update Report to the UNFCCC (2015) will be discussed. These documents will be assessed for the presence of CPI based on the language/drafting of the documents as well as the degree of subject matter regarding CPI expressed in the documents. Based on the analysis, the researcher will propose solutions on how to improve Malaysia’s climate change and energy governance. The theory of reflexive governance will be applied to CPI. The concluding remarks will be about whether CPI reflects reflexive governance by demonstrating how the governance process can be the object of shaping outcomes.

Keywords: climate policy integration, mainstreaming, policy coherence, Malaysian energy governance

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5628 Seismic Inversion for Geothermal Exploration

Authors: E. N. Masri, E. Takács

Abstract:

Amplitude Versus Offset (AVO) and simultaneous model-based impedance inversion techniques have not been utilized for geothermal exploration commonly; however, some recent publications called the attention that they can be very useful in the geothermal investigations. In this study, we present rock physical attributes obtained from 3D pre-stack seismic data and well logs collected in a study area of the NW part of Pannonian Basin where the geothermal reservoir is located in the fractured zones of Triassic basement and it was hit by three productive-injection well pairs. The holes were planned very successfully based on the conventional 3D migrated stack volume prior to this study. Subsequently, the available geophysical-geological datasets provided a great opportunity to test modern inversion procedures in the same area. In this presentation, we provide a summary of the theory and application of the most promising seismic inversion techniques from the viewpoint of geothermal exploration. We demonstrate P- and S-wave impedance, as well as the velocity (Vp and Vs), the density, and the Vp/Vs ratio attribute volumes calculated from the seismic and well-logging data sets. After a detailed discussion, we conclude that P-wave impedance and Vp/Vp ratio are the most helpful parameters for lithology discrimination in the study area. They detect the hot water saturated fracture zone very well thus they can be very useful in mapping the investigated reservoir. Integrated interpretation of all the obtained rock-physical parameters is essential. We are extending the above discussed pre-stack seismic tools by studying the possibilities of Elastic Impedance Inversion (EII) for geothermal exploration. That procedure provides two other useful rock-physical properties, the compressibility and the rigidity (Lamé parameters). Results of those newly created elastic parameters will also be demonstrated in the presentation. Geothermal extraction is of great interest nowadays; and we can adopt several methods have been successfully applied in the hydrocarbon exploration for decades to discover new reservoirs and reduce drilling risk and cost.

Keywords: fractured zone, seismic, well-logging, inversion

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5627 Transitioning Teacher Identity during COVID-19: An Australian Early Childhood Education Perspective

Authors: J. Jebunnesa, Y. Budd, T. Mason

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COVID-19 changed the pedagogical expectations of early childhood education as many teachers across Australia had to quickly adapt to new teaching practices such as remote teaching. An important factor in the successful implementation of any new teaching and learning approach is teacher preparation, however, due to the pandemic, the transformation to remote teaching was immediate. A timely question to be asked is how early childhood teachers managed the transition from face-to-face teaching to remote teaching and what was learned through this time. This study explores the experiences of early childhood educators in Australia during COVID-19 lockdowns. Data were collected from an online survey conducted through the official Facebook forum of “Early Childhood Education and Care Australia,” and a constructivist grounded theory methodology was used to analyse the data. Initial research results suggest changing expectations of teachers’ roles and responsibilities during the lockdown, with a significant category related to transitioning teacher identities emerging. The concept of transitioning represents the shift from the role of early childhood educator to educational innovator, essential worker, social worker, and health officer. The findings illustrate the complexity of early childhood educators’ roles during the pandemic.

Keywords: changing role of teachers, constructivist grounded theory, lessons learned, teaching during COVID-19

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5626 Surface Elevation Dynamics Assessment Using Digital Elevation Models, Light Detection and Ranging, GPS and Geospatial Information Science Analysis: Ecosystem Modelling Approach

Authors: Ali K. M. Al-Nasrawi, Uday A. Al-Hamdany, Sarah M. Hamylton, Brian G. Jones, Yasir M. Alyazichi

Abstract:

Surface elevation dynamics have always responded to disturbance regimes. Creating Digital Elevation Models (DEMs) to detect surface dynamics has led to the development of several methods, devices and data clouds. DEMs can provide accurate and quick results with cost efficiency, in comparison to the inherited geomatics survey techniques. Nowadays, remote sensing datasets have become a primary source to create DEMs, including LiDAR point clouds with GIS analytic tools. However, these data need to be tested for error detection and correction. This paper evaluates various DEMs from different data sources over time for Apple Orchard Island, a coastal site in southeastern Australia, in order to detect surface dynamics. Subsequently, 30 chosen locations were examined in the field to test the error of the DEMs surface detection using high resolution global positioning systems (GPSs). Results show significant surface elevation changes on Apple Orchard Island. Accretion occurred on most of the island while surface elevation loss due to erosion is limited to the northern and southern parts. Concurrently, the projected differential correction and validation method aimed to identify errors in the dataset. The resultant DEMs demonstrated a small error ratio (≤ 3%) from the gathered datasets when compared with the fieldwork survey using RTK-GPS. As modern modelling approaches need to become more effective and accurate, applying several tools to create different DEMs on a multi-temporal scale would allow easy predictions in time-cost-frames with more comprehensive coverage and greater accuracy. With a DEM technique for the eco-geomorphic context, such insights about the ecosystem dynamic detection, at such a coastal intertidal system, would be valuable to assess the accuracy of the predicted eco-geomorphic risk for the conservation management sustainability. Demonstrating this framework to evaluate the historical and current anthropogenic and environmental stressors on coastal surface elevation dynamism could be profitably applied worldwide.

Keywords: DEMs, eco-geomorphic-dynamic processes, geospatial Information Science, remote sensing, surface elevation changes,

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5625 Methods for Mitigating Corrosion Caused by Biogenic Sulfuric Acid in Sewerage Systems: State of the Art Review

Authors: M. Cortés, E. Vera, M. Avella

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Corrosion is an imminent process in nature, which affects all types of materials. In sewerage systems, the corrosion process caused by microorganisms, also known as biogenic sulfuric acid attack, has been studied. This affects the structural integrity of the concrete drainage pipes and the sewage treatment plants. This article is a review of research which focuses on the study of how to reduce the production of hydrogen sulfide, how to improve the resistance of concrete through the use of additives and the implementation of antimicrobial techniques to reduce bacterial growth.

Keywords: bactericides, biogenic sulfuric acid, corrosion, concrete, hydrogen sulphide, nano materials, zeolites

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5624 Nano-Sensors: Search for New Features

Authors: I. Filikhin, B. Vlahovic

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We focus on a novel type of detection based on electron tunneling properties of double nanoscale structures in semiconductor materials. Semiconductor heterostructures as quantum wells (QWs), quantum dots (QDs), and quantum rings (QRs) may have energy level structure of several hundred of electron confinement states. The single electron spectra of the double quantum objects (DQW, DQD, and DQR) were studied in our previous works with relation to the electron localization and tunneling between the objects. The wave function of electron may be localized in one of the QDs or be delocalized when it is spread over the whole system. The localizing-delocalizing tunneling occurs when an electron transition between both states is possible. The tunneling properties of spectra differ strongly for “regular” and “chaotic” systems. We have shown that a small violation of the geometry drastically affects localization of electron. In particular, such violations lead to the elimination of the delocalized states of the system. The same symmetry violation effect happens if electrical or magnetic fields are applied. These phenomena could be used to propose a new type of detection based on the high sensitivity of charge transport between double nanostructures and small violations of the shapes. It may have significant technological implications.

Keywords: double quantum dots, single electron levels, tunneling, electron localizations

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5623 A Case Study in Using the Can-Sized Satellite Platforms for Interdisciplinary Problem-Based Learning in Aeronautical and Electronic Engineering

Authors: Michael Johnson, Vincenzo Oliveri

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This work considers an interdisciplinary Problem-Based Learning (PBL) project developed by lecturers from the Aeronautical and Electronic and Computer Engineering departments at the University of Limerick. This “CANSAT” project utilises the CanSat can-sized satellite platform in order to allow students from aeronautical and electronic engineering to engage in a mixed format (online/face-to-face), interdisciplinary PBL assignment using a real-world platform and application. The project introduces students to the design, development, and construction of the CanSat system over the course of a single semester, enabling student(s) to apply their aeronautical and technical skills/capabilities to the realisation of a working CanSat system. In this case study, the CanSat kits are used to pivot the real-world, discipline-relevant PBL goal of designing, building, and testing the CanSat system with payload(s) from a traditional module-based setting to an online PBL setting. Feedback, impressions, benefits, and challenges identified through the semester are presented. Students found the project to be interesting and rewarding, with the interdisciplinary nature of the project appealing to them. Challenges and difficulties encountered are also addressed, with solutions developed between the students and facilitators to overcoming these discussed.

Keywords: problem-based learning, interdisciplinary, engineering, CanSATs

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5622 Phone Number Spoofing Attack in VoLTE 4G

Authors: Joo-Hyung Oh

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The number of service users of 4G VoLTE (voice over LTE) using LTE data networks is rapidly growing. VoLTE based on all-IP network enables clearer and higher-quality voice calls than 3G. It does, however, pose new challenges; a voice call through IP networks makes it vulnerable to security threats such as wiretapping and forged or falsified information. And in particular, stealing other users’ phone numbers and forging or falsifying call request messages from outgoing voice calls within VoLTE result in considerable losses that include user billing and voice phishing to acquaintances. This paper focuses on the threats of caller phone number spoofing in the VoLTE and countermeasure technology as safety measures for mobile communication networks.

Keywords: LTE, 4G, VoLTE, phone number spoofing

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5621 Disaster Management Using Wireless Sensor Networks

Authors: Akila Murali, Prithika Manivel

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Disasters are defined as a serious disruption of the functioning of a community or a society, which involves widespread human, material, economic or environmental impacts. The number of people suffering food crisis as a result of natural disasters has tripled in the last thirty years. The economic losses due to natural disasters have shown an increase with a factor of eight over the past four decades, caused by the increased vulnerability of the global society, and also due to an increase in the number of weather-related disasters. Efficient disaster detection and alerting systems could reduce the loss of life and properties. In the event of a disaster, another important issue is a good search and rescue system with high levels of precision, timeliness and safety for both the victims and the rescuers. Wireless Sensor Networks technology has the capability of quick capturing, processing, and transmission of critical data in real-time with high resolution. This paper studies the capacity of sensors and a Wireless Sensor Network to collect, collate and analyze valuable and worthwhile data, in an ordered manner to help with disaster management.

Keywords: alerting systems, disaster detection, Ad Hoc network, WSN technology

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5620 A Robust Hybrid Blind Digital Image Watermarking System Using Discrete Wavelet Transform and Contourlet Transform

Authors: Nidal F. Shilbayeh, Belal AbuHaija, Zainab N. Al-Qudsy

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In this paper, a hybrid blind digital watermarking system using Discrete Wavelet Transform (DWT) and Contourlet Transform (CT) has been implemented and tested. The implemented combined digital watermarking system has been tested against five common types of image attacks. The performance evaluation shows improved results in terms of imperceptibility, robustness, and high tolerance against these attacks; accordingly, the system is very effective and applicable.

Keywords: discrete wavelet transform (DWT), contourlet transform (CT), digital image watermarking, copyright protection, geometric attack

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5619 Contextual Toxicity Detection with Data Augmentation

Authors: Julia Ive, Lucia Specia

Abstract:

Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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5618 Comparison of Techniques for Detection and Diagnosis of Eccentricity in the Air-Gap Fault in Induction Motors

Authors: Abrahão S. Fontes, Carlos A. V. Cardoso, Levi P. B. Oliveira

Abstract:

The induction motors are used worldwide in various industries. Several maintenance techniques are applied to increase the operating time and the lifespan of these motors. Among these, the predictive maintenance techniques such as Motor Current Signature Analysis (MCSA), Motor Square Current Signature Analysis (MSCSA), Park's Vector Approach (PVA) and Park's Vector Square Modulus (PVSM) are used to detect and diagnose faults in electric motors, characterized by patterns in the stator current frequency spectrum. In this article, these techniques are applied and compared on a real motor, which has the fault of eccentricity in the air-gap. It was used as a theoretical model of an electric induction motor without fault in order to assist comparison between the stator current frequency spectrum patterns with and without faults. Metrics were purposed and applied to evaluate the sensitivity of each technique fault detection. The results presented here show that the above techniques are suitable for the fault of eccentricity in the air gap, whose comparison between these showed the suitability of each one.

Keywords: eccentricity in the air-gap, fault diagnosis, induction motors, predictive maintenance

Procedia PDF Downloads 332
5617 Deep Learning Based Fall Detection Using Simplified Human Posture

Authors: Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif

Abstract:

Falls are one of the major causes of injury and death among elderly people aged 65 and above. A support system to identify such kind of abnormal activities have become extremely important with the increase in ageing population. Pose estimation is a challenging task and to add more to this, it is even more challenging when pose estimations are performed on challenging poses that may occur during fall. Location of the body provides a clue where the person is at the time of fall. This paper presents a vision-based tracking strategy where available joints are grouped into three different feature points depending upon the section they are located in the body. The three feature points derived from different joints combinations represents the upper region or head region, mid-region or torso and lower region or leg region. Tracking is always challenging when a motion is involved. Hence the idea is to locate the regions in the body in every frame and consider it as the tracking strategy. Grouping these joints can be beneficial to achieve a stable region for tracking. The location of the body parts provides a crucial information to distinguish normal activities from falls.

Keywords: fall detection, machine learning, deep learning, pose estimation, tracking

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5616 Deep Learning based Image Classifiers for Detection of CSSVD in Cacao Plants

Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

Abstract:

The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

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5615 DISGAN: Efficient Generative Adversarial Network-Based Method for Cyber-Intrusion Detection

Authors: Hongyu Chen, Li Jiang

Abstract:

Ubiquitous anomalies endanger the security of our system con- stantly. They may bring irreversible damages to the system and cause leakage of privacy. Thus, it is of vital importance to promptly detect these anomalies. Traditional supervised methods such as Decision Trees and Support Vector Machine (SVM) are used to classify normality and abnormality. However, in some case, the abnormal status are largely rarer than normal status, which leads to decision bias of these methods. Generative adversarial network (GAN) has been proposed to handle the case. With its strong generative ability, it only needs to learn the distribution of normal status, and identify the abnormal status through the gap between it and the learned distribution. Nevertheless, existing GAN-based models are not suitable to process data with discrete values, leading to immense degradation of detection performance. To cope with the discrete features, in this paper, we propose an efficient GAN-based model with specifically-designed loss function. Experiment results show that our model outperforms state-of-the-art models on discrete dataset and remarkably reduce the overhead.

Keywords: GAN, discrete feature, Wasserstein distance, multiple intermediate layers

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5614 Students’ Opinions Related to Virtual Classrooms within the Online Distance Education Graduate Program

Authors: Secil Kaya Gulen

Abstract:

Face to face and virtual classrooms that came up with different conditions and environments, but similar purposes have different characteristics. Although virtual classrooms have some similar facilities with face-to-face classes such as program, students, and administrators, they have no walls and corridors. Therefore, students can attend the courses from a distance and can control their own learning spaces. Virtual classrooms defined as simultaneous online environments where students in different places come together at the same time with the guidance of a teacher. Distance education and virtual classes require different intellectual and managerial skills and models. Therefore, for effective use of virtual classrooms, the virtual property should be taken into consideration. One of the most important factors that affect the spread and effective use of the virtual classrooms is the perceptions and opinions of students -as one the main participants-. Student opinions and recommendations are important in terms of providing information about the fulfillment of expectation. This will help to improve the applications and contribute to the more efficient implementations. In this context, ideas and perceptions of the students related to the virtual classrooms, in general, were determined in this study. Advantages and disadvantages of virtual classrooms expected contributions to the educational system and expected characteristics of virtual classrooms have examined in this study. Students of an online distance education graduate program in which all the courses offered by virtual classrooms have asked for their opinions. Online Distance Education Graduate Program has totally 19 students. The questionnaire that consists of open-ended and multiple choice questions sent to these 19 students and finally 12 of them answered the questionnaire. Analysis of the data presented as frequencies and percentages for each item. SPSS for multiple-choice questions and Nvivo for open-ended questions were used for analyses. According to the results obtained by the analysis, participants stated that they did not get any training on virtual classes before the courses; but they emphasize that newly enrolled students should be educated about the virtual classrooms. In addition, all participants mentioned that virtual classroom contribute their personal development and they want to improve their skills by gaining more experience. The participants, who mainly emphasize the advantages of virtual classrooms, express that the dissemination of virtual classrooms will contribute to the Turkish Education System. Within the advantages of virtual classrooms, ‘recordable and repeatable lessons’ and ‘eliminating the access and transportation costs’ are most common advantages according to the participants. On the other hand, they mentioned ‘technological features and keyboard usage skills affect the attendance’ is the most common disadvantage. Participants' most obvious problem during virtual lectures is ‘lack of technical support’. Finally ‘easy to use’, ‘support possibilities’, ‘communication level’ and ‘flexibility’ come to the forefront in the scope of expected features of virtual classrooms. Last of all, students' opinions about the virtual classrooms seems to be generally positive. Designing and managing virtual classrooms according to the prioritized features will increase the students’ satisfaction and will contribute to improve applications that are more effective.

Keywords: distance education, virtual classrooms, higher education, e-learning

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5613 Neo-Filipino: A Study on the Impact of Internet and Mobile Technology on the Identity Formation of Selected Filipino Third Culture Kids (TCKs)

Authors: Erika Mae L. Valencia

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Third Culture Kids (TCKs) are children who experienced a cross-cultural upbringing – being raised and lived outside their parents’ culture. As a result, TCKs experience the difficulty of building and attaining a concrete cultural identity. However, in the context of globalization and the emergence of ICTs, the internet, and mobile technology creates better ways of constructing cultural identities. This study investigates the social and cultural impacts of the internet and mobile technology on the multi-cultural identity development among selected Filipino TCKs. Moreover, this research seeks to understand how the Filipino TCKs form their identity and address their complex issue of belonging with the use of different internet platforms and mobile technology. To explore the lived experiences of Filipino TCKs, this research employs a transcendental phenomenological design. Also, this study uses purposive and snowball sampling and conduct in-depth interviews through Skype, phone call, or face-to-face. This study utilizes Pierre Bourdieu’s social capital as a theoretical lens to gain understanding of the TCKs’ identity formation process in relation to the said ICTs. This research argues that the internet and mobile technology play a significant role in facilitating multi-cultural identity formation of Filipino TCKs, as well as potentially broadening their social network through its various technological platforms.

Keywords: identity, internet, third culture kids, mobile technology

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5612 Audio-Visual Co-Data Processing Pipeline

Authors: Rita Chattopadhyay, Vivek Anand Thoutam

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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

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5611 Paper-Like and Battery Free Sensor Patches for Wound Monitoring

Authors: Xiaodi Su, Xin Ting Zheng, Laura Sutarlie, Nur Asinah binte Mohamed Salleh, Yong Yu

Abstract:

Wound healing is a dynamic process with multiple phases. Rapid profiling and quantitative characterization of inflammation and infection remain challenging. We have developed paper-like battery-free multiplexed sensors for holistic wound assessment via quantitative detection of multiple inflammation and infection markers. In one of the designs, the sensor patch consists of a wax-printed paper panel with five colorimetric sensor channels arranged in a pattern resembling a five-petaled flower (denoted as a ‘Petal’ sensor). The five sensors are for temperature, pH, trimethylamine, uric acid, and moisture. The sensor patch is sandwiched between a top transparent silicone layer and a bottom adhesive wound contact layer. In the second design, a palm-like-shaped paper strip is fabricated by a paper-cutter printer (denoted as ‘Palm’ sensor). This sensor strip carries five sensor regions connected by a stem sampling entrance that enables rapid colorimetric detection of multiple bacteria metabolites (aldehyde, lactate, moisture, trimethylamine, tryptophan) from wound exudate. For both the “\’ Petal’ and ‘Palm’ sensors, color images can be captured by a mobile phone. According to the color changes, one can quantify the concentration of the biomarkers and then determine wound healing status and identify/quantify bacterial species in infected wounds. The ‘Petal’ and ‘Palm’ sensors are validated with in-situ animal and ex-situ skin wound models, respectively. These sensors have the potential for integration with wound dressing to allow early warning of adverse events without frequent removal of the plasters. Such in-situ and early detection of non-healing condition can trigger immediate clinical intervention to facilitate wound care management.

Keywords: wound infection, colorimetric sensor, paper fluidic sensor, wound care

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5610 Exploring Career Guidance Program for Students with Special Needs

Authors: Rahayu Azkiya

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Career guidance is an integral part of education that aims to help students understand their interests, talents, and potential and provide direction in choosing an appropriate career path. Approximately 76 million people are working out of 17 million people with disabilities in 2022, and this number has become a focal point as career guidance is crucial among people with special needs. Therefore, this study explores how the career guidance program is implemented and what challenges are faced by teachers. This study employs a qualitative case study in one of the senior high schools for special needs (SMLB) in Depok, Indonesia. Meanwhile, the data analysis was done through thematic analysis. Data has been obtained through the interviews of two teachers who focused on the physically impaired and deaf. The results of this study show that (1) the school has implemented career guidance well, the students were selected in the first year to look for their talents and interests, and for the second and third years, students are trained to master their abilities. (2) There are still many challenges teachers face in implementing career guidance programs, such as a need for more human resources for both students and teachers, high curriculum demands, and simple facilities that hinder student progress. Therefore, this research shows that every child is unique, so schools must meet the standards of student needs and re-evaluate the various challenges that teachers and students still face. This research is expected to serve as an analysis material for the government's policy towards special needs schools in Indonesia.

Keywords: Students with Special Needs, Career Guidance Program, Implementation, Challenges

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