Search results for: stress database

Authors: Caspar Goeke, Holger Finger, Dorena Diekamp, Peter König

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Online-based research has recently gained increasing attention from various fields of research in the cognitive sciences. Technological advances in the form of online crowdsourcing (Amazon Mechanical Turk), open data repositories (Open Science Framework), and online analysis (Ipython notebook) offer rich possibilities to improve, validate, and speed up research. However, until today there is no cross-platform integration of these subsystems. Furthermore, implementation of online studies still suffers from the complex implementation (server infrastructure, database programming, security considerations etc.). Here we propose and test a new JavaScript framework that enables researchers to conduct any kind of behavioral research in the browser without the need to program a single line of code. In particular our framework offers the possibility to manipulate and combine the experimental stimuli via a graphical editor, directly in the browser. Moreover, we included an action-event system that can be used to handle user interactions, interactively change stimuli properties or store participants’ responses. Besides traditional recordings such as reaction time, mouse and keyboard presses, the tool offers webcam based eye and face-tracking. On top of these features our framework also takes care about the participant recruitment, via crowdsourcing platforms such as Amazon Mechanical Turk. Furthermore, the build in functionality of google translate will ensure automatic text translations of the experimental content. Thereby, thousands of participants from different cultures and nationalities can be recruited literally within hours. Finally, the recorded data can be visualized and cleaned online, and then exported into the desired formats (csv, xls, sav, mat) for statistical analysis. Alternatively, the data can also be analyzed online within our framework using the integrated Ipython notebook. The framework was designed such that studies can be used interchangeably between researchers. This will support not only the idea of open data repositories but also constitutes the possibility to share and reuse the experimental designs and analyses such that the validity of the paradigms will be improved. Particularly, sharing and integrating the experimental designs and analysis will lead to an increased consistency of experimental paradigms. To demonstrate the functionality of the framework we present the results of a pilot study in the field of spatial navigation that was conducted using the framework. Specifically, we recruited over 2000 subjects with various cultural backgrounds and consequently analyzed performance difference in dependence on the factors culture, gender and age. Overall, our results demonstrate a strong influence of cultural factors in spatial cognition. Such an influence has not yet been reported before and would not have been possible to show without the massive amount of data collected via our framework. In fact, these findings shed new lights on cultural differences in spatial navigation. As a consequence we conclude that our new framework constitutes a wide range of advantages for online research and a methodological innovation, by which new insights can be revealed on the basis of massive data collection.

Keywords: cultural differences, crowdsourcing, JavaScript framework, methodological innovation, online data collection, online study, spatial cognition

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Authors: Jennifer Buz, Alvin Spivey

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The most common greenhouse gas emitted through human activities, carbon dioxide (CO2), is naturally consumed by plants during photosynthesis. This process is actively being monetized by companies wishing to offset their carbon dioxide emissions. For example, companies are now able to purchase protections for vegetated land due-to-be clear cut or purchase barren land for reforestation. Therefore, by actively preventing the destruction/decay of plant matter or by introducing more plant matter (reforestation), a company can theoretically offset some of their emissions. One of the biggest issues in the carbon credit market is validating and verifying carbon offsets. There is a need for a system that can accurately and frequently ensure that the areas sold for carbon credits have the vegetation mass (and therefore for carbon offset capability) they claim. Traditional techniques for measuring vegetation mass and determining health are costly and require many person-hours. Orbital Sidekick offers an alternative approach that accurately quantifies carbon mass and assesses vegetation health through satellite hyperspectral imagery, a technique which enables us to remotely identify material composition (including plant species) and condition (e.g., health and growth stage). How much carbon a plant is capable of storing ultimately is tied to many factors, including material density (primarily species-dependent), plant size, and health (trees that are actively decaying are not effectively storing carbon). All of these factors are capable of being observed through satellite hyperspectral imagery. This abstract focuses on speciation. To build a species classification model, we matched pixels in our remote sensing imagery to plants on the ground for which we know the species. To accomplish this, we collaborated with the researchers at the Teakettle Experimental Forest. Our remote sensing data comes from our airborne “Kato” sensor, which flew over the study area and acquired hyperspectral imagery (400-2500 nm, 472 bands) at ~0.5 m/pixel resolution. Coverage of the entire teakettle experimental forest required capturing dozens of individual hyperspectral images. In order to combine these images into a mosaic, we accounted for potential variations of atmospheric conditions throughout the data collection. To do this, we ran an open source atmospheric correction routine called ISOFIT1 (Imaging Spectrometer Optiman FITting), which converted all of our remote sensing data from radiance to reflectance. A database of reflectance spectra for each of the tree species within the study area was acquired using the Teakettle stem map and the geo-referenced hyperspectral images. We found that a wide variety of machine learning classifiers were able to identify the species within our images with high (>95%) accuracy. For the most robust quantification of carbon mass and the best assessment of the health of a vegetated area, speciation is critical. Through the use of high resolution hyperspectral data, ground-truth databases, and complex analytical techniques, we are able to determine the species present within a pixel to a high degree of accuracy. These species identifications will feed directly into our carbon mass model.

Keywords: hyperspectral, satellite, carbon, imagery, python, machine learning, speciation

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Authors: Christina Van Wingerden

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This paper focuses on a sense of belonging, isolation, and the use of a learning management system as a “third space” for connection and community. Given student use of learning management systems (LMS) for courses on campuses, moderate to high use of social media and hand-held devices, the author explores the possibilities of LMS as a third space. The COVID-19 pandemic has exacerbated student experiences of isolation, and research indicates that students who experience a sense of belonging have a greater likelihood for academic retention and success. The impacts on students of an LMS designed for student employee orientation and training were examined through a mixed methods approach, including a survey, individual interviews, and focus groups. The sample involved 250-450 undergraduate student employees at a US northwestern university. The goal of the study was to find out the efficiency and effectiveness of the orientation information for a wide range of student employees from multiple student affairs departments. And unexpected finding emerged within the study in 2015 and was noted again as a finding in the 2017 study. Students reported feeling like they individually connected to the department, and further to the university because of the LMS orientation. They stated they could see themselves as part of the university community and like they belonged. The orientation, through the LMS, was designed for and occurred online (asynchronous), prior to students traveling and beginning university life for the academic year. The students indicated connection and belonging resulting from some of the design features. With the onset of COVID-19 and prolonged sheltering in place in North America, as well as other parts of the world, students have been precluded from physically gathering to educate and learn. COVID-19 essentially paused face-to-face education in 2020. Media, governments, and higher education outlets have been reporting on widespread college student stress, isolation, loneliness, and sadness. In this context, the author conducted a current mixed methods study (online survey, online interviews) of students in advanced degree programs, like Ph.D. and Ed.D. specifically investigating isolation and sense of belonging. As a part of the study a prototype of a Canvas site was experienced by student interviewees for their reaction of this Canvas site prototype as a “third” space. Some preliminary findings of this study are presented. Doctoral students in the study affirmed the potential of LMS as a third space for community and social academic connection.

Keywords: COVID-19, isolation, learning management system, sense of belonging

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Authors: Manjinder Singh, Jasvinder Singh

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Existing theories of Titanic/Liberty ship, Sydney bridge accidents and practical experience generated an interest in developing weldments those has high toughness under sub-zero temperature conditions. The purpose was to protect the joint from undergoing DBT (Ductile to brittle transition), when ambient temperature reach sub-zero levels. Metallurgical improvement such as low carbonization or addition of deoxidization elements like Mn and Si was effective to prevent fracture in weldments (crack) at low temperature. In the present research, an attempt has been made to investigate the reason behind ductile to brittle transition of mild steel weldments when subjected to sub-zero temperatures and method of its mitigation. Nickel is added to weldments using manual metal arc welding (MMAW) preventing the DBT, but progressive reduction in charpy impact values as temperature is lowered. The variation in toughness with respect to nickel content being added to the weld pool is analyzed quantitatively to evaluate the rise in toughness value with increasing nickel amount. The impact performance of welded specimens was evaluated by Charpy V-notch impact tests at various temperatures (20 °C, 0 °C, -20 °C, -40 °C, -60 °C). Notch is made in the weldments, as notch sensitive failure is particularly likely to occur at zones of high stress concentration caused by a notch. Then the effect of nickel to weldments is investigated at various temperatures was studied by mechanical and metallurgical tests. It was noted that a large gain in impact toughness could be achieved by adding nickel content. The highest yield strength (462J) in combination with good impact toughness (over 220J at – 60 °C) was achieved with an alloying content of 16 wt. %nickel. Based on metallurgical behavior it was concluded that the weld metals solidify as austenite with increase in nickel. The microstructure was characterized using optical and high resolution SEM (scanning electron microscopy). At inter-dendritic regions mainly martensite was found. In dendrite core regions of the low carbon weld metals a mixture of upper bainite, lower bainite and a novel constituent coalesced bainite formed. Coalesced bainite was characterized by large bainitic ferrite grains with cementite precipitates and is believed to form when the bainite and martensite start temperatures are close to each other. Mechanical properties could be rationalized in terms of micro structural constituents as a function of nickel content.

Keywords: MMAW, Toughness, DBT, Notch, SEM, Coalesced bainite

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Authors: A. Isahakyan, A. Terzyan, V. Stepanyan, N. Zulumyan, H. Beglaryan

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The involvement of silica hydrogel derived from serpentine minerals (Mg(Fe))6[Si4O10](OH)8 as a source of silicon dioxide in SiO2–NaOH–BaCl2–H2O system results in precipitating via one-hour stirring of boiling suspension such intermediates that on heating up to 800 °C crystallize into the product composed of barium ortho- Ba2SiO4 and metasilicates BaSiO3. Based on the positive results, this approach has been decided to be adapted to inserting europium (III) ions into the structure of the synthesized compounds. Intermediates previously precipitated in silica hydrogel–NaOH–BaCl2–Eu(NO3)3 system via one-hour stirring at room temperature underwent one-hour heat-treatment at different temperatures (6001200 °C). Prior to calcination, the suspension produced in the mixer was heated on a boiling-water bath until a powder-like sample was obtained. When the silica hydrogel was metered, SiO2 content in the silica hydrogel that is 5.8 % was taken into consideration in order to guaranty the molar ratios of both SiO2 to BaO and SiO2 to Na2O equal to 1:2. BaCl2 and Eu(NO3)3 reagents were weighted so that the formation of appropriate compositions was guaranteed. Samples including various concentrations of Eu3+ ions (1.25, 2.5, 3.75, 5, 6.35, 8.65, 10, 17.5, 18.75 and 20 mol%) were synthesized by the described method. Luminescence excitation, emission spectra of the products were recorded on the Agilent Cary Eclipes fluorescence spectrophotometer using Agilent Xenon flash lamp (80 Hz) as the excitation source (scanning rate=30 nm/min, excitation and emission slits width=5 nm, excitation filter set to auto, emission filter set to auto and PMT detector Voltage=800 V). Prior to optical properties measurements, each of the powder samples was put in the solid sample-holder. X-ray powder diffraction (XRPD) measurements were made on the SmartLab SE diffractometer. Emission spectra recorded for all the samples at an excitation wavelength of 394 nm exhibit peaks centered at around 536, 555, 587, 614, 653, 690 and 702.5 nm. The most intensive emission peak is observed at 614nm due to 5D0→7F2 of europium (III) ions transition. Luminescence intensity achieves its maximum for Eu3+ 17.5 mol% and heat-treatment at 1200 °C. The XRPD patterns revealed that the diffraction peaks recorded for this sample are identical to NaBa6Nd(SiO4)4 reflections. As Nd-containing reagents were not involved into the synthesis, the maximum luminescent intensity is most likely to be conditioned by NaBa6Eu(SiO4)4 formation whose reflections are not available in the ICDD-JCPDS database of crystallographic 2024. Up to Eu3+ 2.5 mol% the samples demonstrate the phases corresponding to Ba2SiO4 and BaSiO3 standards. Subsequent increasing of europium (III) concentration in the system leads to NaBa6Eu(SiO4)4 formation along with Ba2SiO4 and BaSiO3. NaBa6Eu(SiO4)4 share gradually increases and starting from 17.5 mol% and more NaBa6Eu(SiO4)4 phase is only registered. Thus, the variation of europium (III) concentration in silica hydrogel–NaOH–BaCl2–Eu(NO3)3 system allows producing by the precipitation method the products composed of europium (III)-doped Ba2SiO4 and BaSiO3 and/or NaBa6Eu(SiO4)4 distinguished by different luminescent properties. The work was supported by the Science Committee of RA, in the frames of the research projects № 21T-1D131 and № 21SCG-1D013.

Keywords: europium (III)-doped barium ortho- Ba2SiO4 and metasilicates BaSiO₃, NaBa₆Eu(SiO₄)₄, luminescence, precipitation method

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Authors: Camilo Cerda Sarabia, Fernanda Bravo Cornejo, Diego Santibanez Oyarce, Hugo Osses Prado, Esteban Gómez Terán, Belén Diaz Diaz, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Antimicrobial resistance (AMR) represents a significant and rapidly escalating global health threat. Projections estimate that by 2050, AMR infections could claim up to 10 million lives annually. Respiratory infections, in particular, pose a severe risk not only to individual patients but also to the broader public health system. Despite the alarming rise in resistant respiratory infections, AMR within the lung microbiome (microbial community) remains underexplored and poorly characterized. The lungs, as a complex and dynamic microbial environment, host diverse communities of microorganisms whose interactions and resistance mechanisms are not fully understood. Unlike studies that focus on individual genomes, analyzing the entire microbiome provides a comprehensive perspective on microbial interactions, resistance gene transfer, and community dynamics, which are crucial for understanding AMR. However, this holistic approach introduces significant computational challenges and exposes the limitations of traditional analytical methods such as the difficulty of identifying the AMR. Machine learning has emerged as a powerful tool to overcome these challenges, offering the ability to analyze complex genomic data and uncover novel insights into AMR that might be overlooked by conventional approaches. This study investigates microbial resistance within the lung microbiome using unsupervised machine learning approaches to uncover resistance patterns and potential clinical associations. it downloaded and selected lung microbiome data from HumanMetagenomeDB based on metadata characteristics such as relevant clinical information, patient demographics, environmental factors, and sample collection methods. The metadata was further complemented by details on antibiotic usage, disease status, and other relevant descriptions. The sequencing data underwent stringent quality control, followed by a functional profiling focus on identifying resistance genes through specialized databases like Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. Subsequent analyses employed unsupervised machine learning techniques to unravel the structure and diversity of resistomes in the microbial community. Some of the methods employed were clustering methods such as K-Means and Hierarchical Clustering enabled the identification of sample groups based on their resistance gene profiles. The work was implemented in python, leveraging a range of libraries such as biopython for biological sequence manipulation, NumPy for numerical operations, Scikit-learn for machine learning, Matplotlib for data visualization and Pandas for data manipulation. The findings from this study provide insights into the distribution and dynamics of antimicrobial resistance within the lung microbiome. By leveraging unsupervised machine learning, we identified novel resistance patterns and potential drivers within the microbial community.

Keywords: antibiotic resistance, microbial community, unsupervised machine learning., sequences of AMR gene

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Authors: Lucille Alonso, Florent Renard

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The characterizations of urban heat island (UHI) and their interactions with climate change and urban climates are the main research and public health issue, due to the increasing urbanization of the population. These solutions require a better knowledge of the UHI and micro-climate in urban areas, by combining measurements and modelling. This study is part of this topic by evaluating microclimatic conditions in dense urban areas in the Lyon Metropolitan Area (France) using a combination of data traditionally used such as topography, but also from LiDAR (Light Detection And Ranging) data, Landsat 8 satellite observation and Sentinel and ground measurements by bike. These bicycle-dependent weather data collections are used to build the database of the variable to be modelled, the air temperature, over Lyon’s hyper-center. This study aims to model the air temperature, measured during 6 mobile campaigns in Lyon in clear weather, using multiple linear regressions based on 33 explanatory variables. They are of various categories such as meteorological parameters from remote sensing, topographic variables, vegetation indices, the presence of water, humidity, bare soil, buildings, radiation, urban morphology or proximity and density to various land uses (water surfaces, vegetation, bare soil, etc.). The acquisition sources are multiple and come from the Landsat 8 and Sentinel satellites, LiDAR points, and cartographic products downloaded from an open data platform in Greater Lyon. Regarding the presence of low, medium, and high vegetation, the presence of buildings and ground, several buffers close to these factors were tested (5, 10, 20, 25, 50, 100, 200 and 500m). The buffers with the best linear correlations with air temperature for ground are 5m around the measurement points, for low and medium vegetation, and for building 50m and for high vegetation is 100m. The explanatory model of the dependent variable is obtained by multiple linear regression of the remaining explanatory variables (Pearson correlation matrix with a |r| < 0.7 and VIF with < 5) by integrating a stepwise sorting algorithm. Moreover, holdout cross-validation is performed, due to its ability to detect over-fitting of multiple regression, although multiple regression provides internal validation and randomization (80% training, 20% testing). Multiple linear regression explained, on average, 72% of the variance for the study days, with an average RMSE of only 0.20°C. The impact on the model of surface temperature in the estimation of air temperature is the most important variable. Other variables are recurrent such as distance to subway stations, distance to water areas, NDVI, digital elevation model, sky view factor, average vegetation density, or building density. Changing urban morphology influences the city's thermal patterns. The thermal atmosphere in dense urban areas can only be analysed on a microscale to be able to consider the local impact of trees, streets, and buildings. There is currently no network of fixed weather stations sufficiently deployed in central Lyon and most major urban areas. Therefore, it is necessary to use mobile measurements, followed by modelling to characterize the city's multiple thermal environments.

Keywords: air temperature, LIDAR, multiple linear regression, surface temperature, urban heat island

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Authors: Paul Holmes, Mike N. G.

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Foundation-year doctors face increased stress, pressure and uncertainty when starting new rotations throughout their first years of work. This research questionnaire resulted in an induction cheat sheet and induction video that enhanced the Junior doctor's understanding of how to work effectively within the plastic surgery department at NHS Tayside. The objectives and goals were to improve the transition between cohorts of junior doctors in ward 26 at Ninewells Hospital. Before this quality improvement project, the induction pack was 74 pages long and over eight years old. With the support of consultant Mike Ng a new up-to-date induction was created. This involved a questionnaire and cheat sheet being developed. The questionnaire covered clerking, venipuncture, ward pharmacy, theatres, admissions, specialties on the ward, the cardiac arrest trolley, clinical emergencies, discharges and escalation. This audit has three completed cycles between August 2022 and August 2023. The cheat sheet developed a concise two-page A4 document designed for doctors to be able to reference easily and understand the essentials. The document format is a table containing ward layout; specialty; location; physician associate, shift patterns; ward rounds; handover location and time; hours coverage; senior escalation; nights; daytime duties, meetings/MDTs/board meetings, important bleeps and codes; department guidelines; boarders; referrals and patient stream; pharmacy; absences; rota coordinator; annual leave; top tips. The induction video is a 10-minute in-depth explanation of all aspects of the ward. The video explores in more depth the contents of the cheat sheet. This alternative visual format familiarizes the junior doctor with all aspects of the ward. These were provided to all foundation year 1 and 2 doctors on ward 26 at Ninewells Hospital at NHS Tayside Scotland. This work has since been adopted by the General Surgery Department, which extends to six further wards and has improved the effective handing over of the junior doctor’s role between cohorts. There is potential to further expand the cheat sheet to other departments as the concise document takes around 30 minutes to complete by a doctor who is currently on that ward. The time spent filling out the form provides vital information to the incoming junior doctors, which has a significant possibility to improve patient care.

Keywords: induction, junior doctor, handover, plastic surgery

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Authors: John Mark King

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Beginning on Feb. 7, 2019, the luxury brand, Gucci, was met with a firestorm on social media over fashion runway images of its black balaclava sweater, which covered the bottom half of the face and featured large, shiny bright red lips surrounding the mouth cutout. Many observers on social media and in the news media noted the garment resembled racist “blackface.” This study aimed to measure how items were framed across multiple media platforms. The unit of analysis was any headline or lead paragraph published using the search terms “Gucci” and “sweater” or “jumper” or “balaclava” during the one-year timeframe of Feb. 7, 2019, to Feb. 6, 2020. Limitations included headlines and lead paragraphs published in English and indexed in the Lexis/Nexis database. Independent variables were the nation in which the item was published and the platform (newspapers, blogs, web-based publications, newswires, magazines, or broadcast news). Dependent variables were tone toward Gucci (negative, neutral or positive) and frame (blackface/racism/racist, boycott/celebrity boycott, sweater/balaclava/jumper/fashion, apology/pulling the product/diversity initiatives by Gucci or frames unrelated to the controversy but still involving Gucci sweaters) and word count. Two coders achieved 100% agreement on all variables except tone (94.2%) and frame (96.3%). The search yielded 276 items published from 155 sources in 18 nations. The tone toward Gucci during this period was negative (69.9%). Items that were neutral (16.3%) or positive (13.8%) toward the brand were overwhelmingly related to items about other Gucci sweaters worn by celebrities or fashion reviews of other Gucci sweaters. The most frequent frame was apology/pulling the product/diversity initiatives by Gucci (35.5%). The tone was most frequently negative across all continents, including the Middle East (83.3% negative), Asia (81.8%), North America (76.6%), Australia/New Zealand (66.7%), and Europe (59.8%). Newspapers/magazines/newswires/broadcast news transcripts (72.4%) were more negative than blogs/web-based publications (63.6%). The most frequent frames used by newspapers/magazines/newswires/broadcast news transcripts were apology/pulling the product/diversity initiatives by Gucci (38.7%) and blackface/racism/racist (26.1%). Blogs/web-based publications most frequently used frames unrelated to the controversial garment, but about other Gucci sweaters (42.9%) and apology/pulling the product/diversity initiatives by Gucci (27.3%). Sources in Western nations (34.7%) and Eastern nations (47.1%) most frequently used the frame of apology/pulling the product/diversity initiatives by Gucci. Mean word count was higher for negative items (583.58) than positive items (404.76). Items framed as blackface/racism/racist or boycott/celebrity boycott had higher mean word count (668.97) than items framed as sweater/balaclava/jumper/fashion or apology/pulling the product/diversity initiatives by Gucci (498.22). The author concluded that during the year-long period, Gucci’s image was likely damaged by the release of the garment at the center of the controversy due to near-universally negative items published, but Gucci’s apology/pulling the product off the market/diversity initiatives by Gucci and items about other Gucci sweaters worn by celebrities or fashion reviews of other Gucci sweaters were the most common frames across multiple media platforms, which may have mitigated the damage to the brand.

Keywords: Blackface, branding, Gucci, media framing

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Authors: Ahmed Alghurabi, Mysara Mohyaldinn, Shiferaw Jufar, Obai Younis, Abdullah Abduljabbar

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Erosion modeling equations were typically acquired from regulated experimental trials for solid particles entrained in single-phase or multi-phase flows. Evidently, those equations were later employed to predict the erosion damage caused by the continuous impacts of solid particles entrained in streamflow. It is also well-known that the particle impact angle and velocity do not change drastically in gas-sand flow erosion prediction; hence an accurate prediction of erosion can be projected. On the contrary, high-density fluid flows, such as water flow, through complex geometries, such as sand screens, greatly affect the sand particles’ trajectories/tracks and consequently impact the erosion rate predictions. Particle tracking models and erosion equations are frequently applied simultaneously as a method to improve erosion visualization and estimation. In the present work, computational fluid dynamic (CFD)-based erosion modeling was performed using a commercially available software; ANSYS Fluent. The continuous phase (water flow) behavior was simulated using the realizable K-epsilon model, and the secondary phase (solid particles), having a 5% flow concentration, was tracked with the help of the discrete phase model (DPM). To accomplish a successful erosion modeling, three erosion equations from the literature were utilized and introduced to the ANSYS Fluent software to predict the screen wire-slot velocity surge and estimate the maximum erosion rates on the screen surface. Results of turbulent kinetic energy, turbulence intensity, dissipation rate, the total pressure on the screen, screen wall shear stress, and flow velocity vectors were presented and discussed. Moreover, the particle tracks and path-lines were also demonstrated based on their residence time, velocity magnitude, and flow turbulence. On one hand, results from the utilized erosion equations have shown similarities in screen erosion patterns, locations, and DPM concentrations. On the other hand, the model equations estimated slightly different values of maximum erosion rates of the wire-wrapped screen. This is solely based on the fact that the utilized erosion equations were developed with some assumptions that are controlled by the experimental lab conditions.

Keywords: CFD simulation, erosion rate prediction, material loss due to erosion, water-sand flow

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Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

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The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

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Authors: Priyanka Bharti

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Decades ago designs were based on common sense and tradition, but after an enhancement in visualization technology and research, we are now able to comprehend the cognitive ability involved in the decoding of the visual information. However, many fields in visuals need intense research to deliver an efficient explanation for the events. Visuals are an information representation mode through images, symbols and graphics. It plays an impactful role in decision making by facilitating quick recognition, comprehension, and analysis of a situation. They enhance problem-solving capabilities by enabling the processing of more data without overloading the decision maker. As research proves that, visuals offer an improved learning environment by a factor of 400 compared to textual information. Visual information engages learners at a cognitive level and triggers the imagination, which enables the user to process the information faster (visuals are processed 60,000 times faster in the brain than text). Appropriate information, visualization, and its presentation are known to aid and intensify the decision-making process for the users. However, most literature discusses the role of visual aids in comprehension and decision making during normal conditions alone. Unlike emergencies, in a normal situation (e.g. our day to day life) users are neither exposed to stringent time constraints nor face the anxiety of survival and have sufficient time to evaluate various alternatives before making any decision. An emergency is an unexpected probably fatal real-life situation which may inflict serious ramifications on both human life and material possessions unless corrective measures are taken instantly. The situation demands the exposed user to negotiate in a dynamic and unstable scenario in the absence or lack of any preparation, but still, take swift and appropriate decisions to save life/lives or possessions. But the resulting stress and anxiety restricts cue sampling, decreases vigilance, reduces the capacity of working memory, causes premature closure in evaluating alternative options, and results in task shedding. Limited time, uncertainty, high stakes and vague goals negatively affect cognitive abilities to take appropriate decisions. More so, theory of natural decision making by experts has been understood with far more depth than that of an ordinary user. Therefore, in this study, the author aims to understand the role of visual aids in supporting rapid comprehension to take appropriate decisions during an emergency situation.

Keywords: cognition, visual, decision making, graphics, recognition

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Authors: Blanka Havlickova

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In the last ten years, there are growing numbers of troops with machine guns serving on streets of European cities. We can see them around government buildings, major transport hubs, synagogues, galleries and main tourist landmarks. As the main purpose of armed soldier’s presence in European cities authorities declare the prevention of terrorist attacks and psychological support for tourists and domestic population. The main objective of the following study is to find out whether the deployment of armed soldiers in European cities has a calming and reassuring effect on Czech citizens (if the presence at armed soldiers make the Czech population feel more secure) or rather becomes a stress factor (the presence of soldiers standing guard in full military fatigues recalls serious criminality and terrorist attacks which are reflected in the fears and insecurity of Czech population). The initial hypothesis of this study is connected with the priming theory, the idea that when we are exposed to an image (armed soldier), it makes us unconsciously focus on a topic connected with this image (terrorism). This paper is based on a quantitative public survey, which was carried out in the form of electronic questioning among the citizens of the Czech Republic. Respondents answered 14 questions about two European cities – London and Paris. Besides general questions investigating the respondents' awareness of these cities, some of the questions focused on the fear that the respondents had when picturing themselves leaving next Monday for the given city (London or Paris). The questions asking about respondent´s travel fears and concerns were accompanied by different photos. When answering the question about fear some respondents have been presented with a photo of Westminster Palace and the Eiffel with ordinary citizens while other respondents have been presented with a picture of the Westminster Palace, the and Eiffel's tower not only with ordinary citizens, but also with one soldier holding a machine gun. The main goal of this paper is to analyse and compare data about concerns for these two groups of respondents (presented with different pictures) and find out if and how an armed soldier with a machine gun in front of the Westminster Palace or the Eiffel Tower affects the public's concerns about visiting the site. In other words, the aim of this paper is to confirm or rebut the hypothesis that the look at a soldier with a machine gun in front of the Eiffel Tower or the Westminster Palace automatically triggers the association with a terrorist attack leading to an increase in fear and insecurity among Czech population.

Keywords: terrorism, security measures, priming, risk perception

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Authors: Guohong Wang, Hao Huang, Rui Xing, Liyan Tang, Yu Wang

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Start-ups are consistently under pressure to overcome liabilities of newness and smallness. They must focus on assembling resource and engaging constant renewal and repeated entrepreneurial activities to survive and grow. As an important form of resource, knowledge is constantly vital to start-ups, which will help start-ups with developing new product in hence forming competitive advantage. However, significant knowledge is usually needed to be identified and exploited from external entities, which makes it difficult to achieve knowledge transfer; with limited resources, it can be quite challenging for start-ups balancing the exploration and exploitation of knowledge. The research on knowledge transfer has become a relatively well-developed domain by indicating that knowledge transfer can be achieved through plenty of patterns, yet it is still under-explored that what processes and organizational practices help start-ups facilitating knowledge transfer for new product in the context portfolio entrepreneurship. Resource orchestration theory emphasizes the initiative and active management of company or the manager to explain the fulfillment of resource utility, which will help understand the process of managing knowledge as a certain kind of resource in start-ups. Drawing on the resource orchestration theory, this research aims to explore how knowledge transfer can be facilitated through resource orchestration. A qualitative single-case study of a sodium-ion battery new venture was conducted. The case company is sampled deliberately from representative industrial agglomeration areas in Liaoning Province, China. It is found that distinctive resource orchestration sub-processes are leveraged to facilitate knowledge transfer: (i) resource structuring makes knowledge available across the portfolio; (ii) resource bundling makes combines internal and external knowledge to form new knowledge; and (iii) resource harmonizing balances specific knowledge configurations across the portfolio. Meanwhile, by purposefully reallocating knowledge configurations to new product development in a certain new venture (exploration) and gradually adjusting knowledge configurations to being applied to existing products across the portfolio (exploitation), resource orchestration processes as a whole make exploration and exploitation of knowledge balanced. This study contributes to the knowledge management literature through proposing a resource orchestration view and depicting how knowledge transfer can be facilitated through different resource orchestration processes and mechanisms. In addition, by revealing the balancing process of exploration and exploitation of knowledge, and laying stress on the significance of the idea of making exploration and exploitation of knowledge balanced in the context of portfolio entrepreneurship, this study also adds specific efforts to entrepreneurship and strategy management literature.

Keywords: exploration and exploitation, knowledge transfer, new product development, portfolio entrepreneur, resource orchestration

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Authors: Chukwuka Justus Iwegbu

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Background: A major concern facing the world is providing senior citizens, individuals with disabilities, and other vulnerable groups with high-quality care. This issue is more serious in Nigeria's North Eastern area, where the burden of disease and disability is heavy, and access to care is constrained. This study aims to fill this gap by exploring the roles, challenges and support needs of caregivers, care home management, funding and administration in challenged communities in North Eastern Nigeria. The study will also provide a comprehensive understanding of the current situation and identify opportunities for improving the quality of care and support for caregivers and care recipients in these communities. Methods: A mixed-methods design, including both quantitative and qualitative data collection methods, will be used, and it will be guided by the stress process model of caregiving. The qualitative stage approach will comprise a survey, In-depth interviews, observations, and focus group discussion and the quantitative analysis will be used in order to comprehend the variations between caregiver's roles and care home management. A review of relevant documents, such as care home policies and funding reports, would be used to gather quantitative data on the administrative and financial aspects of care. The data collected will be analyzed using both descriptive statistics and thematic analysis. A sample size of around 200-300 participants, including caregivers, care recipients, care home managers and administrators, policymakers and health care providers, would be recruited. Findings: The study revealed that caregivers in challenged communities in North Eastern Nigeria face significant challenges, including lack of training and support, limited access to funding and resources, and high levels of burnout. Care home management and administration were also found to be inadequate, with a lack of clear policies and procedures and limited oversight and accountability. Conclusion: There is a need for increased investment in training and support for caregivers, as well as a need for improved care home management and administration in challenged communities in North Eastern Nigeria. It also highlights the importance of involving community members in decision-making and planning processes related to care homes and services. The study would contribute to the existing body of knowledge by providing a detailed understanding of the challenges faced by caregivers, care home managers and administrators.

Keywords: caregivers, care home management, funding, administration, challenge communities, North Eastern Nigeria

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Authors: Hussah Alotaishan

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In today’s globally-driven modern cities diverse groups of new visitors face various challenges when attempting to find their desired location if culture and language are barriers. The most common way-showing tools such as directional and identificational signs are the most problematic and their usefulness can be limited or even non-existent. It is argued new methods should be implemented that could support or replace such conventional literacy and language dependent way-finding aids. It has been concluded in recent research studies that local urban features in complex pedestrian spaces are worthy of further study in order to reveal if they do function as way-showing clues. Some researchers propose a more comprehensive approach to the complex perception of buildings, façade design and surface patterns, while some have been questioning whether we necessarily need directional signs or can other methods deliver the same message but in a clearer manner for a wider range of users. This study aimed to test to what extent do existent environmental and urban features through the city center area of Swansea in the UK facilitate the way-finding process of a first time visitor. The three-hour experiment was set to attempt to find 11 visitor attractions ranging from recreational, historical, educational and religious locations. The challenge was attempting to find as many as possible when no prior geographical knowledge of their whereabouts was established. The only clues were 11 pictures representing each of the locations that had been acquired from the city of Swansea official website. An iPhone and a heart-rate tracker wristwatch were used to record the route was taken and stress levels, and take record photographs of destinations or decision-making points throughout the journey. This paper addresses: current limitations in understanding the ways that the physical environment can be intentionally deployed to facilitate pedestrians while finding their way around, without or with a reduction in language dependent signage; investigates visitor perceptions of their surroundings by indicating what urban elements manifested an impact on the way-finding process. The initial findings support the view that building facades and street features, such as width, could facilitate the decision-making process if strategically employed. However, more importantly, the anticipated features of a specific place construed from a promotional picture can also be misleading and create confusion that may lead to getting lost.

Keywords: pedestrian way-finding, environmental features, urban way-showing, environmental affordance

Procedia PDF Downloads 173

Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Nowadays, wetlands are the subject of contradictory debates opposing scientific, political and administrative meanings. Indeed, given their multiple services (drinking water, irrigation, hydrological regulation, mineral, plant and animal resources...), wetlands concentrate many socio-economic and biodiversity issues. In some regions, they can cover vast areas (>100 thousand ha) of the landscape, such as the Camargue area in the south of France, inside the Rhone delta. The high biological productivity of wetlands, the strong natural selection pressures and the diversity of aquatic environments have produced many species of plants and animals that are found nowhere else. These environments are tremendous carbon sinks and biodiversity reserves depending on their age, composition and surrounding environmental conditions, wetlands play an important role in global climate projections. Covering more than 3% of the earth's surface, wetlands have experienced since the beginning of the 1990s a tremendous revival of interest, which has resulted in the multiplication of inventories, scientific studies and management experiments. The geographical and physical characteristics of the wetlands of the central region conceal a large number of natural habitats that harbour a great biological diversity. These wetlands, one of the natural habitats, are still influenced by human activities, especially agriculture, which affects its layout and functioning. In this perspective, decision-makers need to delimit spatial objects (natural habitats) in a certain way to be able to take action. Thus, wetlands are no exception to this rule even if it seems to be a difficult exercise to delimit a type of environment as whose main characteristic is often to occupy the transition between aquatic and terrestrial environment. However, it is possible to map wetlands with databases, derived from the interpretation of photos and satellite images, such as the European database Corine Land cover, which allows quantifying and characterizing for each place the characteristic wetland types. Scientific studies have shown limitations when using high spatial resolution images (SPOT, Landsat, ASTER) for the identification and characterization of small wetlands (1 hectare). To address this limitation, it is important to note that these wetlands generally represent spatially complex features. Indeed, the use of very high spatial resolution images (>3m) is necessary to map small and large areas. However, with the recent evolution of artificial intelligence (AI) and deep learning methods for satellite image processing have shown a much better performance compared to traditional processing based only on pixel structures. Our research work is also based on spectral and textural analysis on THR images (Spot and IRC orthoimage) using two object-oriented approaches, the nearest neighbour approach (k-NN) and the Super Vector Machine approach (SVM). The k-NN approach gave good results for the delineation of wetlands (wet marshes and moors, ponds, artificial wetlands water body edges, ponds, mountain wetlands, river edges and brackish marshes) with a kappa index higher than 85%.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: Adeline Stals

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The transformation of architectural design practices has been underway for almost forty years due to the development and democratization of computer technology. New and more efficient tools are constantly being proposed to architects, amplifying a technological wave that sometimes stimulates them, sometimes overwhelms them, depending essentially on their digital culture and the context (socio-economic, structural, organizational) in which they work on a daily basis. Our focus is on VR, AR, and MR technologies dedicated to architecture. The commercialization of affordable headsets like the Oculus Rift, the HTC Vive or more low-tech like the Google CardBoard, makes it more accessible to benefit from these technologies. In that regard, researchers report the growing interest of these tools for architects, given the new perspectives they open up in terms of workflow, representation, collaboration, and client’s involvement. However, studies rarely mention the consequences of the sample studied on results. Our research provides an overview of VR, AR, and MR researches among a corpus of papers selected from conferences and journals. A closer look at the sample of these research projects highlights the necessity to take into consideration the context of studies in order to develop tools truly dedicated to the real practices of specific architect profiles. This literature review formalizes milestones for future challenges to address. The methodology applied is based on a systematic review of two sources of publications. The first one is the Cumincad database, which regroups publications from conferences exclusively about digital in architecture. Additionally, the second part of the corpus is based on journal publications. Journals have been selected considering their ranking on Scimago. Among the journals in the predefined category ‘architecture’ and in Quartile 1 for 2018 (last update when consulted), we have retained the ones related to the architectural design process: Design Studies, CoDesign, Architectural Science Review, Frontiers of Architectural Research and Archnet-IJAR. Beside those journals, IJAC, not classified in the ‘architecture’ category, is selected by the author for its adequacy with architecture and computing. For all requests, the search terms were ‘virtual reality’, ‘augmented reality’, and ‘mixed reality’ in title and/or keywords for papers published between 2015 and 2019 (included). This frame time is defined considering the fast evolution of these technologies in the past few years. Accordingly, the systematic review covers 202 publications. The literature review on studies about XR technologies establishes the state of the art of the current situation. It highlights that studies are mostly based on experimental contexts with controlled conditions (pedagogical, e.g.) or on practices established in large architectural offices of international renown. However, few studies focus on the strategies and practices developed by offices of smaller size, which represent the largest part of the market. Indeed, a European survey studying the architectural profession in Europe in 2018 reveals that 99% of offices are composed of less than ten people, and 71% of only one person. The study also showed that the number of medium-sized offices is continuously decreasing in favour of smaller structures. In doing so, a frontier seems to remain between the worlds of research and practice, especially for the majority of small architectural practices having a modest use of technology. This paper constitutes a reference for the next step of the research and for further worldwide researches by facilitating their contextualization.

Keywords: architectural design, literature review, SME, XR technologies

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Authors: Nurlan Smagulov, Aiman Konkabayeva, Akerke Sadykova, Arailym Serik

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Introduction. Adverse environmental factors do not immediately lead to pathological changes in the body. They can exert the growth of pre-pathology characterized by shifts in physiological, biochemical, immunological and other indicators of the body state. These disorders are unstable, reversible and indicative of body reactions. There is an opportunity to objectively judge the internal structure of the adaptive body reactions at the level of individual organs and systems. In order to obtain a stable response of the body to the chronic effects of unfavorable environmental factors of low intensity (compared to production environment factors), a time called the «lag time» is needed. The obtained results without considering this factor distort reality and, for the most part, cannot be a reliable statement of the main conclusions in any work. A technique is needed to reduce methodological errors and combine mathematical logic using statistical methods and a medical point of view, which ultimately will affect the obtained results and avoid a false correlation. Objective. Development of a methodology for assessing and predicting the environmental factors impact on the population health considering the «lag time.» Methods. Research objects: environmental and population morbidity indicators. The database on the environmental state was compiled from the monthly newsletters of Kazhydromet. Data on population morbidity were obtained from regional statistical yearbooks. When processing static data, a time interval (lag) was determined for each «argument-function» pair. That is the required interval, after which the harmful factor effect (argument) will fully manifest itself in the indicators of the organism's state (function). The lag value was determined by cross-correlation functions of arguments (environmental indicators) with functions (morbidity). Correlation coefficients (r) and their reliability (t), Fisher's criterion (F) and the influence share (R2) of the main factor (argument) per indicator (function) were calculated as a percentage. Results. The ecological situation of an industrially developed region has an impact on health indicators, but it has some nuances. Fundamentally opposite results were obtained in the mathematical data processing, considering the «lag time». Namely, an expressed correlation was revealed after two databases (ecology-morbidity) shifted. For example, the lag period was 4 years for dust concentration, general morbidity, and 3 years – for childhood morbidity. These periods accounted for the maximum values of the correlation coefficients and the largest percentage of the influencing factor. Similar results were observed in relation to the concentration of soot, dioxide, etc. The comprehensive statistical processing using multiple correlation-regression variance analysis confirms the correctness of the above statement. This method provided the integrated approach to predicting the degree of pollution of the main environmental components to identify the most dangerous combinations of concentrations of leading negative environmental factors. Conclusion. The method of assessing the «environment-public health» system (considering the «lag time») is qualitatively different from the traditional (without considering the «lag time»). The results significantly differ and are more amenable to a logical explanation of the obtained dependencies. The method allows presenting the quantitative and qualitative dependence in a different way within the «environment-public health» system.

Keywords: ecology, morbidity, population, lag time

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Authors: Amin Akbari, Dongcai Wang, Huiru Li, Xiaoping Du, Jie Chen

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The effect of vibrational force (VF) on accelerating orthodontic tooth movement depends on the level of delivered stimulation to the tooth in terms of peak load (PL), which requires contacts between the tooth and the VF device. A personalized device ensures the contacts, but the resulting PL distribution on the teeth is unknown. Furthermore, it is unclear whether the PL on particular teeth can be adjusted to the prescribed values. The objective of this study was to investigate the efficacy of apersonalized VF device in controlling the level of stimulation on two teeth, the mandibular canines and 2nd molars. A 3-D finite element (FE) model of human dentition, including teeth, PDL, and alveolar bone, was created from the cone beam computed tomography images of an anonymous subject. The VF was applied to the teeth through a VFdevice consisting of a mouthpiece with engraved tooth profile of the subject and a VF source that applied 0.3 N force with the frequency of 30 Hz. The dentition and mouthpiece were meshed using 10-node tetrahedral elements. Interface elements were created at the interfaces between the teeth and the mouthpiece. The upper and lower teeth bite on the mouthpiece to receive the vibration. The depth of engraved individual tooth profile could be adjusted, which was accomplished by adding a layer of material as an interference or removing a layer of material as a clearance to change the PL on the tooth. The interference increases the PL while the clearance decreases it. Fivemouthpiece design cases were simulated, which included a mouthpiece without interference/clearance; the mouthpieces with bilateral interferences on both mandibular canines and 2nd molars with magnitudes of 0.1, 0.15, and 0.2-mm, respectively; and mouthpiece with bilateral 0.3-mm clearances on the four teeth. Then, the force distributions on the entire dentition were compared corresponding to these adjustments. The PL distribution on the teeth is uneven when there is no interference or clearance. Among all teeth, the anterior segment receives the highest level of PL. Adding 0.1, 0.15, and 0.2-mm interferences to the canines and 2nd molars bilaterally leads to increase of the PL on the canines by 10, 62, and 73 percent and on the 2nd molar by 14, 55, and 87 percent, respectively. Adding clearances to the canines and 2nd molars by removing the contactsbetween these teeth and the mouthpiece results in zero PL on them. Moreover, introducing interference to mandibular canines and 2nd molarsredistributes the PL on the entireteeth. The share of the PL on the anterior teeth are reduced. The use of the personalized mouthpiece ensures contactsof the teeth to the mouthpiece so that all teeth can be stimulated. However, the PL distribution is uneven. Adding interference between a tooth and the mouthpiece increases the PL while introducing clearance decreases the PL. As a result, the PL is redistributed. This study confirms that the level of VF stimulation on the individual tooth can be adjusted to a prescribed value.

Keywords: finite element method, orthodontic treatment, stress analysis, tooth movement, vibrational force

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Authors: Eunsu Jang, Kang Park

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In developing an armored ground combat vehicle (AGCV), it is a very important step to analyze the vulnerability (or the survivability) of the AGCV against enemy’s attack. In the vulnerability analysis, the penetration equations are usually used to get the penetration depth and check whether a bullet can penetrate the armor of the AGCV, which causes the damage of internal components or crews. The penetration equations are derived from penetration experiments which require long time and great efforts. However, they usually hold only for the specific material of the target and the specific type of the bullet used in experiments. Thus, penetration simulation using ANSYS can be another option to calculate penetration depth. However, it is very important to model the targets and select the input parameters in order to get an accurate penetration depth. This paper performed a sensitivity analysis of input parameters of ANSYS on the accuracy of the calculated penetration depth. Two conflicting objectives need to be achieved in adopting ANSYS in penetration analysis: maximizing the accuracy of calculation and minimizing the calculation time. To maximize the calculation accuracy, the sensitivity analysis of the input parameters for ANSYS was performed and calculated the RMS error with the experimental data. The input parameters include mesh size, boundary condition, material properties, target diameter are tested and selected to minimize the error between the calculated result from simulation and the experiment data from the papers on the penetration equation. To minimize the calculation time, the parameter values obtained from accuracy analysis are adjusted to get optimized overall performance. As result of analysis, the followings were found: 1) As the mesh size gradually decreases from 0.9 mm to 0.5 mm, both the penetration depth and calculation time increase. 2) As diameters of the target decrease from 250mm to 60 mm, both the penetration depth and calculation time decrease. 3) As the yield stress which is one of the material property of the target decreases, the penetration depth increases. 4) The boundary condition with the fixed side surface of the target gives more penetration depth than that with the fixed side and rear surfaces. By using above finding, the input parameters can be tuned to minimize the error between simulation and experiments. By using simulation tool, ANSYS, with delicately tuned input parameters, penetration analysis can be done on computer without actual experiments. The data of penetration experiments are usually hard to get because of security reasons and only published papers provide them in the limited target material. The next step of this research is to generalize this approach to anticipate the penetration depth by interpolating the known penetration experiments. This result may not be accurate enough to be used to replace the penetration experiments, but those simulations can be used in the early stage of the design process of AGCV in modelling and simulation stage.

Keywords: ANSYS, input parameters, penetration depth, sensitivity analysis

Procedia PDF Downloads 401

Authors: Kaushal Kishore, Suman Mukhopadhyay, Susovan Das, Manashi Adhikary, Sandip Bhattacharyya

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In integrated steel plants, conveyor belts are widely used for transferring raw materials from one location to another. An output pin bush coupling attached with a conveyor transferring iron ore fines and fluxes failed after two years of service life. This led to an operational delay of approximately 15 hours. This study is focused on failure analysis of the coupling and recommending counter-measures to prevent any such failures in the future. Investigation consisted of careful visual observation, checking of operating parameters, stress calculation and analysis, macro and micro-fractography, material characterizations like chemical and metallurgical analysis and tensile and impact testings. The fracture occurred from an unusually sharp double step. There were multiple corrosion pits near the step that aggravated the situation. Inner contact surface of the coupling revealed differential abrasion that created a macroscopic difference in the height of the component. This pointed towards misalignment of the coupling beyond a threshold limit. In addition to these design and installation issues, material of the coupling did not meet the quality standards. These were made up of grey cast iron having graphite morphology intermediate between random distribution (Type A) and rosette pattern (Type B). This manifested as a marked reduction in impact toughness and tensile strength of the component. These findings corroborated well with the brittle mode of fracture that might have occurred during minor impact loading while loading of conveyor belt with raw materials from height. Simulated study was conducted to examine the effect of corrosion pits on tensile and impact toughness of grey cast iron. It was observed that pitting marginally reduced tensile strength and ductility. However, there was marked (up to 45%) reduction in impact toughness due to pitting. Thus, it became evident that failure of the coupling occurred due to combination of factors like inferior material, misalignment, poor step design and corrosion pitting. Recommendation for life enhancement of coupling included the use of tougher SG 500/7 grade, incorporation of proper fillet radius for the step, correction of alignment and application of corrosion resistant organic coating to prevent pitting.

Keywords: brittle fracture, cast iron, coupling, double step, pitting, simulated impact tests

Procedia PDF Downloads 132

Authors: Lamia Bouzgarrou, Amira Omrane, Haithem Kalel, Salma Kammoun

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Background: During recent decades, mechanical and electrical industrial sector has greatly expanded with a significant employability potential. However, this sector faces the increasing prevalence of musculoskeletal disorders with heavy consequences associated with direct and indirect costs. Objective: The current intervention was motivated by large musculoskeletal upper limbs and back disorders frequency among the operators of an assembly workshop in a leader company specialized in sanitary equipment and water and gas connections. We aimed to identify biomechanical constraints among these operators through activity and biomechanical exposures semi-quantitative analysis based on video recordings and MUSKA-TMS software. Methods: We conducted, open observations and exploratory interviews at first, in order to overall understand work situation. Then, we analyzed operator’s activity through systematic observations and interviews. Finally, we conducted a semi-quantitative biomechanical constraints analysis with MUSKA-TMS software after representative activity period video recording. The assessment of biomechanical constrains was based on different criteria; biomechanical characteristics (work positions), aggravating factor (cold, vibration, stress, etc.) and exposure time (duration and frequency of solicitations, recovery phase); with a synthetic score of risk level variable from 1 to 4 (1: low risk of developing MSD and 4: high risk). Results: Semi-quantitative analysis objective many elementary operations with higher biomechanical constrains like high repetitiveness, insufficient recovery time and constraining angulation of shoulders, wrists and cervical spine. Among these risky elementary operations we sited the assembly of sleeve with the body, the assembly of axis, and the control on testing table of gas valves. Transformation of work situations were recommended, covering both the redevelopment of industrial areas and the integration of new tools and equipment of mechanical handling that reduces operator exposure to vibration. Conclusion: Musculoskeletal disorders are complex and costly disorders. Moreover, an approach centered on the observation of the work can promote the interdisciplinary dialogue and exchange between actors with the objective to maximize the performance of a company and improve the quality of life of operators.

Keywords: musculoskeletal disorders, biomechanical constrains, semi-quantitative analysis, ergonomics

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Authors: Eva Nolan, Timothy Mcnichols

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Gamers spend over 3 billion hours collectively playing video games a week, which is arguably not nearly enough time to indulge in the many benefits gaming has to offer. Much of the previous research on video gaming is centered on the effects of playing violent video games and the negative impacts they have on the individual. However, there is a dearth of research in the area of non-violent video games, specifically the emotional and cognitive benefits playing non-violent games can offer individuals. Current research in the area of video game play suggests there are many benefits to playing for an individual, such as decreasing symptoms of depression, decreasing stress, increasing positive emotions, inducing relaxation, decreasing anxiety, and particularly improving mood. One suggestion as to why video games may offer such benefits is that they possess ideal characteristics to create and maintain flow experiences, which in turn, is the subjective experience where an individual obtains a heightened and improved state of mind while they are engaged in a task where a balance of challenge and skill is found. Many video games offer a platform for collaborative gameplay, which can enhance the emotional experience of gaming through the feeling of social support and social inclusion. The present study was designed to examine the effects of collaborative gameplay and flow experience on participants’ perceived mood. To investigate this phenomenon, an in-between subjects design involving forty participants were randomly divided into two groups where they engaged in solo or collaborative gameplay. Each group represented an even number of frequent gamers and non-frequent gamers. Each participant played ‘The Lego Movie Videogame’ on the Playstation 4 console. The participant’s levels of flow experience and perceived mood were measured by the Flow State Scale (FSS) and the Positive and Negative Affect Schedule (PANAS). The following research hypotheses were investigated: (i.) participants in the collaborative gameplay condition will experience higher levels of flow experience and higher levels of mood than those in the solo gameplay condition; (ii.) participants who are frequent gamers will experience higher levels of flow experience and higher levels of mood than non-frequent gamers; and (iii.) there will be a significant positive relationship between flow experience and mood. If the estimated findings are supported, this suggests that engaging in collaborative gameplay can be beneficial for an individual’s mood and that experiencing a state of flow can also enhance an individual’s mood. Hence, collaborative gaming can be beneficial to promote positive emotions (higher levels of mood) through engaging an individual’s flow state.

Keywords: collaborative gameplay, flow experience, mood, games, positive emotions

Procedia PDF Downloads 335

Authors: Fatna Benmessaoud, Mohammed Cheikh, Vencent Velay, Vanessa Vidal, Farhad Rezai-Aria, Christine Boher

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Ti-6Al-4V titanium alloy is one of the most widely used materials in aeronautical and aerospace industries. Because of its high specific strength, good fatigue, and corrosion resistance, this alloy is very suitable for moderate temperature applications. At room temperature, Ti-6Al-4V mechanical behavior is generally controlled by the behavior of alpha phase (beta phase percent is less than 8%). The plastic strain of this phase notably based on crystallographic slip can be hindered by various obstacles and mechanisms (crystal lattice friction, sessile dislocations, strengthening by solute atoms and grain boundaries…). The grains aspect of alpha phase (its morphology and texture) and the nature of its crystallographic lattice (which is hexagonal compact) give to plastic strain heterogeneous, discontinuous and anisotropic characteristics at the local scale. The aim of this work is to develop a multi-scale model for Ti-6Al-4V mechanical behavior using crystal plasticity approach; this multi-scale model is used then to investigate grains size, dispersion of grains size, crystallographic texture and slip systems activation effects on Ti-6Al-4V mechanical behavior under monotone quasi-static loading. Nine representative elementary volume (REV) are built for taking into account the physical elements (grains size, dispersion and crystallographic) mentioned above, then boundary conditions of tension test are applied. Finally, simulation of the mechanical behavior of Ti-6Al-4V and study of slip systems activation in alpha phase is reported. The results show that the macroscopic mechanical behavior of Ti-6Al-4V is strongly linked to the active slip systems family (prismatic, basal or pyramidal). The crystallographic texture determines which family of slip systems can be activated; therefore it gives to the plastic strain a heterogeneous character thus an anisotropic macroscopic mechanical behavior of Ti-6Al-4V alloy modeled. The grains size influences also on mechanical proprieties of Ti-6Al-4V, especially on the yield stress; by decreasing of the grain size, the yield strength increases. Finally, the grains' distribution which characterizes the morphology aspect (homogeneous or heterogeneous) gives to the deformation fields distribution enough heterogeneity because the crystallographic slip is easier in large grains compared to small grains, which generates a localization of plastic deformation in certain areas and a concentration of stresses in others.

Keywords: multi-scale modeling, Ti-6Al-4V alloy, crystal plasticity, grains size, crystallographic texture

Procedia PDF Downloads 157

Authors: Yuan-Hao Lee, Chia-Wei Lee, Ming-Fang Lin, Tzu-Huei Wu, Chih-Hsiang Ko, Wing P. Chan

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Computed tomography (CT) scan of the head is a good method for investigating cranial lesions. However, radiation-induced oxidative stress can be accumulated in the eyes and promote carcinogenesis and cataract. In this regard, we aimed to protect the eyes with barium sulfate shield(s) during CT scans and investigate the resultant image quality and radiation dose to the eye. Patients who underwent health examinations were selectively enrolled in this study in compliance with the protocol approved by the Ethics Committee of the Joint Institutional Review Board at Taipei Medical University. Participants’ brains were scanned with a water-based marker simultaneously by a multislice CT scanner (SOMATON Definition Flash) under a fixed tube current-time setting or automatic tube current modulation (TCM). The lens dose was measured by Gafchromic films, whose dose response curve was previously fitted using thermoluminescent dosimeters, with or without barium sulfate or bismuth-antimony shield laid above. For the assessment of image quality CT images at slice planes that exhibit the interested regions on the zygomatic, orbital and nasal bones of the head phantom as well as the water-based marker were used for calculating the signal-to-noise and contrast-to-noise ratios. The application of barium sulfate and bismuth-antimony shields decreased 24% and 47% of the lens dose on average, respectively. Under topogram-based TCM, the dose saving power of bismuth-antimony shield was mitigated whereas that of barium sulfate shield was enhanced. On the other hand, the signal-to-noise and contrast-to-noise ratios of DSCT images were decreased separately by barium sulfate and bismuth-antimony shield, resulting in an overall reduction of the CNR. In contrast, the integration of topogram-based TCM elevated signal difference between the ROIs on the zygomatic bones and eyeballs while preferentially decreasing the signal-to-noise ratios upon the use of barium sulfate shield. The results of this study indicate that the balance between eye exposure and image quality can be optimized by combining eye shields with topogram-based TCM on the multislice scanner. Eye shielding could change the photon attenuation characteristics of tissues that are close to the shield. The application of both shields on eye protection hence is not recommended for seeking intraorbital lesions.

Keywords: computed tomography, barium sulfate shield, dose saving, image quality

Procedia PDF Downloads 268

Authors: Ghada Ben Brahim, Aicha El Rabia, Mohamed Hedi Inoubli

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Climate change has exacerbated disparities in the distribution of water resources in Tunisia, resulting in significant degradation in quantity and quality over the past five decades. The Mio-Plio-Quaternary aquifer, the primary water source in the Zarzis region, is subject to climatic, geographical, and geological challenges, as well as human stress. The region is experiencing uneven distribution and growing threats from groundwater salinity and saltwater intrusion. Addressing this challenge is critical for the arid region’s socioeconomic development, and effective water resource management is required to combat climate change and reduce water deficits. This study uses a multidisciplinary approach to determine the groundwater potential of this aquifer, involving geophysics and hydrogeology data analysis. We used advanced techniques such as 3D Euler deconvolution and power spectrum analysis to generate detailed anomaly maps and estimate the depths of density sources, identifying significant Bouguer anomalies trending E-W, NW-SE, and NE-SW. Various techniques, such as wavelength filtering, upward continuation, and horizontal and vertical derivatives, were used to improve the gravity data, resulting in consistent results for anomaly shapes and amplitudes. The Euler deconvolution method revealed two prominent surface faults, trending NE-SW and NW-SE, that have a significant impact on the distribution of sedimentary facies and water quality within the Mio-Plio-Quaternary aquifer. Additionally, depth maxima greater than 1400 m to the North indicate the presence of a Cretaceous paleo-fault. Geoelectrical models and resistivity pseudo-sections were used to interpret the distribution of electrical facies in the Mio-Plio-Quaternary aquifer, highlighting lateral variation and depositional environment type. AI optimises the analysis and interpretation of exploration data, which is important to long-term management and water security. Machine learning algorithms and deep learning models analyse large datasets to provide precise interpretations of subsurface conditions, such as aquifer salinisation. However, AI has limitations, such as the requirement for large datasets, the risk of overfitting, and integration issues with traditional geological methods.

Keywords: mio-plio-quaternary aquifer, Southeastern Tunisia, geophysical methods, hydrogeological analysis, artificial intelligence

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Authors: Zakiullah Kalwar, Shabeer Abbassi

Abstract:

This research encompasses the study of structural styles and evaluation of the hydrocarbon potential of Kotrum and Drigri anticlines located in Rajanpur Area, Midddle Indus Basin of Pakistan with the approach of geophysical data integration. The study area is situated between the Sulaiman Foldbelt on the west and Indus River in the east. It is an anticlinal fold, located to the southeast of Sakhi Sarwar anticline and separated from a prominent syncline. The structure has a narrow elongated crest, with the axis running in SSW-NNE direction. In the east, the structure is bounded by a gentle syncline. Structural Styles are trending East-West and perpendicular to tectonic transport and stress direction and the base of the structures gradually dipping Eastward beneath the deformation frontal part in Eastern Sulaiman Fold Belt. Middle Indus Basin can be divided into Foreland, Sulaiman fold belt and a broad foredeep. Sulaiman represents a blind thrust front, which suggests that all frontal folds of the fold belt are cored by blind thrust. The deformation of frontal part of Sulaiman Lobe represents the passive roof duplex stacked beneath the frontal passive roof thrust. The passive roof thrust, which has a back thrust sense of motion and extends into the interior of Fold belt. Left lateral Kingri Fault separates Eastern and Central Sulaiman fold belt. In Central Sulaiman fold belt the deformation front moved further towards fore deep as compared to Eastern Sulaiman. Two wells (Kotrum-01, Drigri-01) have been drilled in the study area with the objective to determine the potential of oil and gas in Habib Rahi Limestone of Eocene age, Dunghan Limestone of Paleocene age and Pab Sandstone of cretaceous age and role of structural styles in hydrocarbon potential of study area. Kotrum-01 well was drilled to its T.D of 4798m. Besides fishing and side tracking, tight whole conditions, high pressure, and losses of circulation were also encountered. During production, testing Pab sandstone were tested but abandoned found. Drigri-01 well was drilled to its T.D 3250 m. RFT was carried out at different points, but all points showed no pressure / seal failure and the well was plugged and declared abandoned.

Keywords: hydrocarbon potential, structural style, reserve calculation, enhance production

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Authors: Laura Micheli, Majd Hijazi, Mahmoud Faytarouni

Abstract:

The damage reported by oil and gas industrial facilities revealed the utmost vulnerability of steel liquid storage tanks to seismic events. The failure of steel storage tanks may yield devastating and long-lasting consequences on built and natural environments, including the release of hazardous substances, uncontrolled fires, and soil contamination with hazardous materials. It is, therefore, fundamental to reliably predict the damage that steel liquid storage tanks will likely experience under future seismic hazard events. The seismic performance of steel liquid storage tanks is usually assessed using vulnerability curves obtained from the numerical simulation of a tank under different hazard scenarios. However, the computational demand of high-fidelity numerical simulation models, such as finite element models, makes the vulnerability assessment of liquid storage tanks time-consuming and often impractical. As a solution, this paper presents a surrogate model-based strategy for predicting seismic-induced damage in steel liquid storage tanks. In the proposed strategy, the surrogate model is leveraged to reduce the computational demand of time-consuming numerical simulations. To create the data set for training the surrogate model, field damage data from past earthquakes reconnaissance surveys and reports are collected. Features representative of steel liquid storage tank characteristics (e.g., diameter, height, liquid level, yielding stress) and seismic excitation parameters (e.g., peak ground acceleration, magnitude) are extracted from the field damage data. The collected data are then utilized to train a surrogate model that maps the relationship between tank characteristics, seismic hazard parameters, and seismic-induced damage via a data-driven surrogate model. Different types of surrogate algorithms, including naïve Bayes, k-nearest neighbors, decision tree, and random forest, are investigated, and results in terms of accuracy are reported. The model that yields the most accurate predictions is employed to predict future damage as a function of tank characteristics and seismic hazard intensity level. Results show that the proposed approach can be used to estimate the extent of damage in steel liquid storage tanks, where the use of data-driven surrogates represents a viable alternative to computationally expensive numerical simulation models.

Keywords: damage prediction , data-driven model, seismic performance, steel liquid storage tanks, surrogate model

Procedia PDF Downloads 143

Authors: Güllü Yakar, Adnan Tepecik

Abstract:

A university campus resembles an independent city that is spread over a wide area. Campuses that incorporate thousands of new domestic and international users at the beginning of every academic period also host scientific, cultural and sportive events, in addition to embodying regular users such as students and staff. Wayfinding and signage systems are necessary for the regulation of vehicular traffic, and they enable users’ to navigate without losing time or feeling anxiety. While designing the system or testing the functionality of it, opinions of existing users or likely behaviors of typical user profiles (personas) provide designers with insight. The purpose of this study is to identify the wayfinding attitudes and expectations of Kastamonu University Kuzeykent Campus users. This study applies a mixed method in which a questionnaire, developed by the researcher, constitute the quantitative phase of the study. The survey was carried out with 850 participants who filled a questionnaire form which was tested in terms of construct validity by using Exploratory Factor Analysis. While interpreting the data obtained, Chi-Square, T- Test and ANOVA analyses were applied as well as descriptive analyses such as frequency (f) and percentage (%) values. The results of this survey, which was conducted during the absence of systematic wayfinding signs in the campus, reveals the participants expectations for insertion of floor plans and wayfinding signs to indoors, maps to outdoors, symbols and color codes to the existing signs and for the adequate arrangement of those for the use of visually impaired people. The fact that there is a direct proportional relation between the length of institution membership and wayfinding competency within campus, leads to the conclusion that especially the new comers are in need of wayfinding signs. In order to determine the effectiveness of campus-wide wayfinding system implemented after the survey and in order to identify the further expectations of users in this respect, a semi-structured interview form developed by the researcher and assessments of 20 participants are compiled. Subjected to content analysis, this data constitute the qualitative dimension of the study. Research results indicate that despite the presence of the signs, the participants experienced either inability or stress while finding their way, showed tendency to receive help from others and needed outdoor maps and signs, in addition to bigger-sized texts.

Keywords: environmental graphic design, environmental perception, wayfinding and signage design, wayfinding system

Procedia PDF Downloads 237