Search results for: virtual domain

Authors: Jenn Gallup, Onur Kocaoz, Onder Islek

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In their pursuit of postsecondary transitions, individuals with disabilities tend to experience, academic, behavioral, and emotional challenges to a greater extent than their typically developing peers. These challenges result in lower rates of graduation, employment, independent living, and participation in college than their peers without disabilities. The lack of friendships and support systems has had a negative impact on those with a disability transitioning to postsecondary settings to include, employment, independent living, and university settings. Establishing friendships and support systems early on is an indicator of potential success and persistence in postsecondary education, employment, and independent living for typically developing college students. It is evident that a deficit in friendships and supports is a key deficit also for individuals with disabilities. To address the specific needs of this group, a mentor program was developed for a transition program held at the university for youth aged 18-21. Pre-service teachers enrolled in the special education program engaged with youth in the transition program in a variety of activities on campus. The mentorship program had two purposes: to assist young adults with disabilities who were transitioning to a workforce setting to help increase social skills, self-advocacy, supports and friendships, and confidence; and to give their peers without disabilities who were enrolled in a secondary special education course as a pre-service teacher the experience of interacting with and forming friendships with peers who had a disability for the purposes of career development. Additionally, according to researchers mobile technology has created a virtual world of equality and opportunity for a large segment of the population that was once marginalized due to physical and cognitive impairments. All of the participants had access to smart phones; therefore, technology was explored during this study to determine if it could be used as a compensatory tool to allow the young adults with disabilities to do things that otherwise would have been difficult because of their disabilities. Additionally, all participants were asked to incorporate technology such as smart phones to communicate beyond the activities, collaborate using virtual platform games which would support and promote social skills, soft-skills, socialization, and relationships. The findings of this study confirmed that a peer mentorship program that harnessed the power of technology supported outcomes specific to young adults with and without disabilities. Mobile technology and virtual game-based platforms, were identified as a significant contributor to personal, academic, and career growth for both groups. The technology encouraged friendships, provided an avenue for rich social interactions, and increased soft-skills. Results will be shared along with the development of the program and potential implications to the field.

Keywords: career outcomes, mentorship, soft-skills, technology, transition

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Authors: Jixiang Lei, Alexander Fuchs, Franz Pernkopf, Katrin Ellermann

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Within the Space@Sea project, funded by the Horizon 2020 program, an island consisting of multiple platforms was designed. The platforms are connected by ropes and fenders. The connection is critical with respect to the safety of the whole system. Therefore, fault detection systems are investigated, which could detect early warning signs for a possible failure in the connection elements. Previously, a model-based method called Extended Kalman Filter was developed to detect the reduction of rope stiffness. This method detected several types of faults reliably, but some types of faults were much more difficult to detect. Furthermore, the model-based method is sensitive to environmental noise. When the wave height is low, a long time is needed to detect a fault and the accuracy is not always satisfactory. In this sense, it is necessary to develop a more accurate and robust technique that can detect all rope faults under a wide range of operational conditions. Inspired by this work on the Space at Sea design, we introduce a fault diagnosis method based on deep neural networks. Our method cannot only detect rope degradation by using the acceleration data from each platform but also estimate the contributions of the specific acceleration sensors using methods from explainable AI. In order to adapt to different operational conditions, the domain adaptation technique DANN is applied. The proposed model can accurately estimate rope degradation under a wide range of environmental conditions and help users understand the relationship between the output and the contributions of each acceleration sensor.

Keywords: fault diagnosis, deep learning, domain adaptation, explainable AI

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Authors: Shady Adib, Vladimir Vinogradov, Peter Gosling

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Digital Twin (DT) technology is a new technology that appeared in the early 21st century. The DT is defined as the digital representation of living and non-living physical assets. By connecting the physical and virtual assets, data are transmitted smoothly, allowing the virtual asset to fully represent the physical asset. Although there are lots of studies conducted on the DT concept, there is still limited information about the ability of the DT models for monitoring and detecting unexpected changes in structural behaviour in real time. This is due to the large computational efforts required for the analysis and an excessively large amount of data transferred from sensors. This paper aims to develop the DT concept to be able to detect the abnormal changes in structural behaviour in real time using advanced modelling techniques, deep learning algorithms, and data acquisition systems, taking into consideration model uncertainties. finite element (FE) models were first developed offline to be used with a reduced basis (RB) model order reduction technique for the construction of low-dimensional space to speed the analysis during the online stage. The RB model was validated against experimental test results for the establishment of a DT model of a two-dimensional truss. The established DT model and deep learning algorithms were used to identify the location of damage once it has appeared during the online stage. Finally, the RB model was used again to identify the damage severity. It was found that using the RB model, constructed offline, speeds the FE analysis during the online stage. The constructed RB model showed higher accuracy for predicting the damage severity, while deep learning algorithms were found to be useful for estimating the location of damage with small severity.

Keywords: data acquisition system, deep learning, digital twin, model uncertainties, reduced basis, reduced order model

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Authors: Mohammad Zaeimzade

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The development of communication technologies is clearly and rapidly moving towards reducing the distance between the virtual and real worlds. Of course, living in a two-spatial or two-globalized world or any other interpretation that means mixing real and virtual life is still relevant and debatable. In the present age of communication, where social networks have transformed the message equation and turned the audience out of passivity and turned into a user. Platforms have penetrated widely in various aspects of human life, from culture and education and economy. Among the messengers, Instagram, which is one of the most extensive image-based interactive networks, plays a significant role in the new economic life. It doesn't need much explanation that the era of thinking of every messenger as a non-insulating conductor that is just a neutral load has passed. Every messenger has its own economic, political and of course security background, Instagram is no exception to this rule and of course it leaves its effects in bio-economics as well. Iran, as the 19th largest economy in the world, has not been unaffected by new platforms, including Instagram, and their consequences in the economy. Generally, in the policy-making space, there are two simple and inflexible pessimistic or optimistic views on this issue, and each of the holders of these views usually have their own one-dimensional policy recommendations regarding how to deal with Instagram. Prescriptions that are usually very different and sometimes contradictory. In this article, we show that this confusion of policymakers is the result of not accurately describing the reality of its effect, and the reason for this inaccurate description is the existence of a conflict of interests in the eyes of describers and researchers. In this article, we first take a look at the main indicators of the Iranian economy, estimate the role of the digital economy in Iran's economic growth, then study the conflicting descriptions of the Instagram-based digital economy, the statistics that show the tolerance of economic users of Instagram in Iran. 300 thousand to 9 million have been estimated. Finally, we take a look at the government's actions in this matter, especially in the context of street riots in October and November 2022. And we suggest an intermediate idea.

Keywords: digital economy, instagram, conflict of interest, social networks

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for the easy creation of an institutional risk profile for endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support risk factors set up with just the most important values that are important for a particular organisation. Subsequently, the risk profile employs fuzzy models and associated configurations for the file format metadata aggregator to support digital preservation experts with a semi-automatic estimation of endangerment level for file formats. Our goal is to make use of a domain expert knowledge base aggregated from a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation and analysis of risk factors for a requried dimension. The proposed methods improve the visibility of risk factor information and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and automatically aggregated file format metadata from linked open data sources. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: digital information management, file format, endangerment analysis, fuzzy models

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Authors: Marta Błażkiewicz, Adam Konefał

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Currently, boron-neutron therapy is carried out mainly with the use of a neutron beam generated in research nuclear reactors. This fact limits the possibility of realization of a BNCT in centers distant from the above-mentioned reactors. Moreover, the number of active nuclear reactors in operation in the world is decreasing due to the limited lifetime of their operation and the lack of new installations. Therefore, the possibilities of carrying out boron-neutron therapy based on the neutron beam from the experimental reactor are shrinking. However, the use of nuclear power reactors for BNCT purposes is impossible due to the infrastructure not intended for radiotherapy. Therefore, a serious challenge is to find ways to perform boron-neutron therapy based on neutrons generated outside the research nuclear reactor. This work meets this challenge. Its goal is to develop a BNCT technique based on commonly available neutron sources such as Cf-252 and PuBe, which will enable the above-mentioned therapy in medical centers unrelated to nuclear research reactors. Advances in the field of neutron source fabrication make it possible to achieve strong neutron fluxes. The current stage of research focuses on the development of virtual models of the above-mentioned sources using the Monte Carlo simulation method. In this study, the GEANT4 tool was used, including the model for simulating neutron-matter interactions - High Precision Neutron. Models of neutron sources were developed on the basis of experimental verification based on the activation detectors method with the use of indium foil and the cadmium differentiation method allowing to separate the indium activation contribution from thermal and resonance neutrons. Due to the large number of factors affecting the result of the verification experiment, the 10% discrepancy between the simulation and experiment results was accepted.

Keywords: BNCT, virtual models, neutron sources, monte carlo, GEANT4, neutron activation detectors, gamma spectroscopy

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Authors: Gizem Kayar, Ramazan Bakir, M. Ilkay Koşar, Ceren U. Gencer, Alperen Ayyildiz

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Anatomy classes are crucial for general education of medical students, whereas learning anatomy is quite challenging and requires memorization of thousands of structures. In traditional teaching methods, learning materials are still based on books, anatomy mannequins, or videos. This results in forgetting many important structures after several years. However, more interactive teaching methods like virtual reality, augmented reality, gamification, and motion sensors are becoming more popular since such methods ease the way we learn and keep the data in mind for longer terms. During our study, we designed a virtual reality based digital head anatomy platform to investigate whether a fully interactive anatomy platform is effective to learn anatomy and to understand the level of teaching and learning optimization. The Head is one of the most complicated human anatomy structures, with thousands of tiny, unique structures. This makes the head anatomy one of the most difficult parts to understand during class sessions. Therefore, we developed a fully interactive digital tool with 3D model marking, quiz structures, 2D/3D puzzle structures, and VR support so as to integrate the power of VR and gamification. The project has been developed in Unity game engine with HTC Vive Cosmos VR headset. The head anatomy 3D model has been selected with full skeletal, muscular, integumentary, head, teeth, lymph, and vein system. The biggest issue during the development was the complexity of our model and the marking of it in the 3D world system. 3D model marking requires to access to each unique structure in the counted subsystems which means hundreds of marking needs to be done. Some parts of our 3D head model were monolithic. This is why we worked on dividing such parts to subparts which is very time-consuming. In order to subdivide monolithic parts, one must use an external modeling tool. However, such tools generally come with high learning curves, and seamless division is not ensured. Second option was to integrate tiny colliders to all unique items for mouse interaction. However, outside colliders which cover inner trigger colliders cause overlapping, and these colliders repel each other. Third option is using raycasting. However, due to its own view-based nature, raycasting has some inherent problems. As the model rotate, view direction changes very frequently, and directional computations become even harder. This is why, finally, we studied on the local coordinate system. By taking the pivot point of the model into consideration (back of the nose), each sub-structure is marked with its own local coordinate with respect to the pivot. After converting the mouse position to the world position and checking its relation with the corresponding structure’s local coordinate, we were able to mark all points correctly. The advantage of this method is its applicability and accuracy for all types of monolithic anatomical structures.

Keywords: anatomy, e-learning, virtual reality, 3D model marking

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Authors: Sung-Jun Yoo, Kazuhide Ito

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In this study, a comprehensive computer simulated person (CSP) that integrates computational human model (virtual manikin) and respiratory tract model (virtual airway), was applied for estimation of indoor environmental quality. Moreover, an inclusive prediction method was established by integrating computational fluid dynamics (CFD) analysis with advanced CSP which is combined with physiologically-based pharmacokinetic (PBPK) model, unsteady thermoregulation model for analysis targeting micro-climate around human body and respiratory area with high accuracy. This comprehensive method can estimate not only the contaminant inhalation but also constant interaction in the contaminant transfer between indoor spaces, i.e., a target area for indoor air quality (IAQ) assessment, and respiratory zone for health risk assessment. This study focused on the usage of the CSP as an air/thermal quality sensor in indoors, which means the application of comprehensive model for assessment of IAQ and thermal environmental quality. Demonstrative analysis was performed in order to examine the applicability of the comprehensive model to the heating, ventilation, air conditioning (HVAC) control scheme. CSP was located at the center of the simple model room which has dimension of 3m×3m×3m. Formaldehyde which is generated from floor material was assumed as a target contaminant, and flow field, sensible/latent heat and contaminant transfer analysis in indoor space were conducted by using CFD simulation coupled with CSP. In this analysis, thermal comfort was evaluated by thermoregulatory analysis, and respiratory exposure risks represented by adsorption flux/concentration at airway wall surface were estimated by PBPK-CFD hybrid analysis. These Analysis results concerning IAQ and thermal comfort will be fed back to the HVAC control and could be used to find a suitable ventilation rate and energy requirement for air conditioning system.

Keywords: CFD simulation, computer simulated person, HVAC control, indoor environmental quality

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Authors: Wondale Getinet Alemu, Lillian Mwanri, Clemence Due, Telake Azale, Anna Ziersch

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Background: Mental illness is one of the most severe, chronic, and disabling public health problems that affect patients' Quality of life (QoL). Improving the QoL for people with mental illness is one of the most critical steps in stopping disease progression and avoiding complications of mental illness. Therefore, we aimed to assess the QoL and its determinants in patients with mental illness in outpatient clinics in Northwest Ethiopia in 2023. Methods: A facility-based cross-sectional study was conducted among people with mental illness in an outpatient clinic in Ethiopia. The sampling interval was decided by dividing the total number of study participants who had a follow-up appointment during the data collection period (2400) by the total sample size of 638, with the starting point selected by lottery method. The interviewer-administered WHOQOL BREF-26 tool was used to measure the QoL of people with mental illness. The domains and Health-Related Quality of Life (HRQoL) were identified. The indirect and direct effects of variables were calculated using structural equation modeling with SPSS-28 and Amos-28 software. A p-value of < 0.05 and a 95% CI were used to evaluate statistical significance. Results: A total of 636 (99.7%) participants responded and completed the WHOQOL-BREF questionnaire. The mean score of overall HRQoL of people with mental illness in the outpatient clinic was (49.6 ± 10 Sd). The highest QoL was found in the physical health domain (50.67 ±9.5 Sd), and the lowest mean QoL was found in the psychological health domain (48.41±10 Sd). Rural residents, drug nonadherence, suicidal ideation, not getting counseling, moderate or severe subjective severity, the family does not participate in patient care, and a family history of mental illness had an indirect negative effect on HRQoL. Alcohol use and psychological health domain had a direct positive effect on QoL. Furthermore, objective severity of illness, having low self-esteem, and having a history of mental illness in the family had both direct and indirect effects on QoL. Furthermore, sociodemographic factors (residence, educational status, marital status), social support-related factors (self-esteem, family not participating in patient care), substance use factors (alcohol use, tobacco use,) and clinical factors (objective and subjective severity of illness, not getting counseling, suicidal ideation, number of episodes, comorbid illness, family history of mental illness, poor drug adherence) directly and indirectly affected QoL. Conclusions: In this study, the QoL of people with mental illness was poor, with the psychological health domain being the most affected. Sociodemographic factors, social support-related factors, drug use factors, and clinical factors directly and indirectly, affect QoL through the mediator variables of physical health domains, psychological health domains, social relation health domains, and environmental health domains. In order to improve the QoL of people with mental illnesses, we recommend that emphasis be given to addressing the scourge of mental health, including the development of policy and practice drivers that address the above-identified factors.

Keywords: quality of life, mental wellbeing, mental illness, mental disorder, Ethiopia

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Authors: Chih-Jer Lin, Jian-Hong Hou

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Industry 4.0 is a vision of integrated industry implemented by artificial intelligent computing, software, and Internet technologies. The main goal of industry 4.0 is to deal with the difficulty owing to competitive pressures in the marketplace. For today’s manufacturing factories, the type of production is changed from mass production (high quantity production with low product variety) to medium quantity-high variety production. To offer flexibility, better quality control, and improved productivity, robot manipulators are used to combine material processing, material handling, and part positioning systems into an integrated manufacturing system. To implement the automated system for sheet metal bending operations, motion planning of a 7-degrees of freedom (DOF) robot is studied in this paper. A virtual reality (VR) environment of a bending cell, which consists of the robot and a bending machine, is established using the virtual robot experimentation platform (V-REP) simulator. For sheet metal bending operations, the robot only needs six DOFs for the pick-and-place or tracking tasks. Therefore, this 7 DOF robot has more DOFs than the required to execute a specified task; it can be called a redundant robot. Therefore, this robot has kinematic redundancies to deal with the task-priority problems. For redundant robots, Pseudo-inverse of the Jacobian is the most popular motion planning method, but the pseudo-inverse methods usually lead to a kind of chaotic motion with unpredictable arm configurations as the Jacobian matrix lose ranks. To overcome the above problem, we proposed a method to formulate the motion planning problems as optimization problem. Moreover, a genetic algorithm (GA) based method is proposed to deal with motion planning of the redundant robot. Simulation results validate the proposed method feasible for motion planning of the redundant robot in an automated sheet-metal bending operations.

Keywords: redundant robot, motion planning, genetic algorithm, obstacle avoidance

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Authors: Sigal Portnoy, Jason Friedman, Eitan Raveh

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Introduction: Sensory substitution is possible due to the capacity of our brain to adapt to information transmitted by a synthetic receptor via an alternative sensory system. Practical sensory substitution systems are being developed in order to increase the functionality of individuals with sensory loss, e.g. amputees. For upper limb prosthetic-users the loss of tactile feedback compels them to allocate visual attention to their prosthesis. The effect of adding vibrotactile feedback (VTF) to the applied force has been studied, however its effect on the allocation if visual attention during dual-tasking and the response during misleading visual feedback have not been studied. We hypothesized that VTF will improve the performance and reduce visual attention during dual-task assignments in healthy individuals using a robotic hand and improve the performance in a standardized functional test, despite the presence of misleading visual feedback. Methods: For the dual-task paradigm, twenty healthy subjects were instructed to toggle two keyboard arrow keys with the left hand to retain a moving virtual car on a road on a screen. During the game, instructions for various activities, e.g. mix the sugar in the glass with a spoon, appeared on the screen. The subject performed these tasks with a robotic hand, attached to the right hand. The robotic hand was controlled by the activity of the flexors and extensors of the right wrist, recorded using surface EMG electrodes. Pressure sensors were attached at the tips of the robotic hand and induced VTF using vibrotactile actuators attached to the right arm of the subject. An eye-tracking system tracked to visual attention of the subject during the trials. The trials were repeated twice, with and without the VTF. Additionally, the subjects performed the modified box and blocks, hidden from eyesight, in a motion laboratory. A virtual presentation of a misleading visual feedback was be presented on a screen so that twice during the trial, the virtual block fell while the physical block was still held by the subject. Results: This is an ongoing study, which current results are detailed below. We are continuing these trials with transradial myoelectric prosthesis-users. In the healthy group, the VTF did not reduce the visual attention or improve performance during dual-tasking for the tasks that were typed transfer-to-target, e.g. place the eraser on the shelf. An improvement was observed for other tasks. For example, the average±standard deviation of time to complete the sugar-mixing task was 13.7±17.2s and 19.3±9.1s with and without the VTF, respectively. Also, the number of gaze shifts from the screen to the hand during this task were 15.5±23.7 and 20.0±11.6, with and without the VTF, respectively. The response of the subjects to the misleading visual feedback did not differ between the two conditions, i.e. with and without VTF. Conclusions: Our interim results suggest that the performance of certain activities of daily living may be improved by VTF. The substitution of visual sensory input by tactile feedback might require a long training period so that brain plasticity can occur and allow adaptation to the new condition.

Keywords: prosthetics, rehabilitation, sensory substitution, upper limb amputation

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Authors: Pratibha Biswal, Suyash Morchhale, Anshuman Singh Yadav, Shubham Sanjay Chobe

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Energy demands are increasing whereas energy sources, especially non-renewable sources are limited. Due to the intermittent nature of renewable energy sources, it has become the need of the hour to find new ways to store energy. Out of various energy storage methods, latent heat thermal storage devices are becoming popular due to their high energy density per unit mass and volume at nearly constant temperature. This work presents a computational fluid dynamics (CFD) model using ANSYS FLUENT 19.0 for energy storage characteristics of a phase change material (PCM) filled in a vertical triplex tube thermal energy storage system. A vertical triplex tube heat exchanger, just like its name consists of three concentric tubes (pipe sections) for parting the device into three fluid domains. The PCM is filled in the middle domain with heat transfer fluids flowing in the outer and innermost domains. To enhance the heat transfer inside the PCM, eight fins have been incorporated between the internal and external tubes. These fins run radially outwards from the outer-wall of innermost tube to the inner-wall of the middle tube dividing the middle domain (between innermost and middle tube) into eight sections. These eight sections are then filled with a PCM. The validation is carried with earlier work and a grid independence test is also presented. Further studies on freezing and melting process were carried out. The results are presented in terms of pictorial representation of isotherms and liquid fraction

Keywords: heat exchanger, thermal energy storage, phase change material, CFD, latent heat

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Authors: Schnell Zsuzsanna

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Background: The interpretation of written texts, language processing in the visual domain, in other words, atypical reading abilities, also known as dyslexia, is an ever-growing phenomenon in today’s societies and educational communities. The much-researched problem affects cognitive abilities and, coupled with normal intelligence normally manifests difficulties in the differentiation of sounds and orthography and in the holistic processing of written words. The factors of susceptibility are varied: social, cognitive psychological, and linguistic factors interact with each other. Methods: The research will explain the psycholinguistics of dyslexia on the basis of several empirical experiments and demonstrate how domain-general abilities of inhibition, retrieval from the mental lexicon, priming, phonological processing, and visual modality transfer affect successful language processing and interpretation. Interpretation of visual stimuli is hindered, and the problem seems to be embedded in a sociocultural, psycholinguistic, and cognitive background. This makes the picture even more complex, suggesting that the understanding and resolving of the issues of dyslexia has to be interdisciplinary, aided by several disciplines in the field of humanities and social sciences, and should be researched from an empirical approach, where the practical, educational corollaries can be analyzed on an applied basis. Aim and applicability: The lecture sheds light on the applied, cognitive aspects of interpretation, social cognitive traits of language processing, the mental underpinnings of cognitive interpretation strategies in different languages (namely, Hungarian and English), offering solutions with a few applied techniques for success in foreign language learning that can be useful advice for the developers of testing methodologies and measures across ESL teaching and testing platforms.

Keywords: dyslexia, social cognition, transparency, modalities

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Authors: Babak Mohajeri

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In recent years, the conventional business model of ownership has been changed towards accessibility in a variety of markets. Two trends can be observed in the evolution of this rental-like business model. Firstly, the technological development that enables the emergence of new business models. These new business models increasingly become agile and flexible. For example Spotify, an online music stream company provides consumers access to over millions of music tracks, conveniently through the smartphone, tablet or computer. Similarly, Car2Go, the car sharing company accesses its members with flexible and nearby sharing cars. The second trend is the increasing communication and connections via social networks. This trend enables a shift to peer-to-peer accessibility based business models. Conventionally, companies provide access for their customers to own companies products or services. In peer-to-peer model, nonetheless, companies facilitate access and connection across their customers to use other customers owned property or skills, competencies or services .The is so-called the sharing economy business model. The aim of this study is to investigate into a new and emerging type of the sharing economy model in which role of customers and service providers may dramatically change. This new model is called Collaborative Service Networks. We propose a mechanism for Collaborative Service Networks business model. Uber and Airbnb, two successful growing companies, have been selected for our case studies and their business models are analyzed. Finally, we study the emergence of the collaborative service networks in the manufacturing domain. Our finding results to a new manufacturing paradigm called social manufacturing.

Keywords: sharing economy, collaborative service networks, social manufacturing, manufacturing development

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Authors: Yi-Hui Lai, Chih-Hsiang Yang, Li-Chung Hsu

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The inflammasome is a protein complex that modulates caspase-1 activity, resulting in proteolytic cleavage of proinflammatory cytokines such as IL-1β and IL-18, into their bioactive forms. It has been shown that the inflammasomes play a crucial role in the clearance of pathogenic infection and tissue repair. However, dysregulated inflammasome activation contributes to a wide range of human diseases such as cancers and auto-inflammatory diseases. Yet, regulation of NLRP3 inflammasome activation remains largely unknown. We discovered a novel DEAD box protein, whose biological function has not been reported, not only negatively regulates NLRP3 inflammasome activation by interfering NLRP3 inflammasome assembly and cellular localization but also mitigate pyroptosis upon pathogen evasion. The DEAD-box protein is the first DEAD-box protein gets involved in modulation of the inflammasome activation. In our study, we found that caspase-1 activation and mature IL-1β production were largely enhanced upon LPS challenge in the DEAD box-containing protein- deleted THP-1 macrophages and bone marrow-derived macrophages (BMDMs). In addition, this DEAD box-containing protein migrates from the nucleus to the cytoplasm upon LPS stimulation, which is required for its inhibitory role in NLRP3 inflammasome activation. The DEAD box-containing protein specifically interacted with the LRR motif of NLRP3 via its DEAD domain. Furthermore, due to the crucial role of the NLRP3 LRR domain in the recruitment of NLRP3 to mitochondria and binding to its adaptor ASC, we found that the interaction of NLRP3 and ASC was downregulated in the presence of the DEAD box-containing protein. In addition to the mechanical study, we also found that this DEAD box protein protects host cells from inflammasome-triggered cell death in response to broad-ranging pathogens such as Candida albicans, Streptococcus pneumoniae, etc., involved in nosocomial infections and severe fever shock. Collectively, our results suggest that this novel DEAD box molecule might be a key therapeutic strategy for various infectious diseases.

Keywords: inflammasome, inflammation, innate immunity, pyroptosis

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Authors: P. Jayashree, S. Rajkumar

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With the trend of virtual and augmented reality environments booming to provide a life like experience, gaming is a major tool in supporting such learning environments. In this work, a variant of Voronoi heuristics, employing supervised learning for the TRON game is proposed. The paper discusses the features that would be really useful when a machine learning bot is to be used as an opponent against a human player. Various game scenarios, nature of the bot and the experimental results are provided for the proposed variant to prove that the approach is better than those that are currently followed.

Keywords: artificial Intelligence, automation, machine learning, TRON game, Voronoi heuristics

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Authors: B. Remya Mohan, Kamal Bijlani, R. Jayakrishnan

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Visualization in an educational context provides the learner with visual means of information. Conceptualizing certain circumstances such as consequences of smoking can be done more effectively with the help of the technology, Augmented Reality (AR). It is a new methodology for effective learning. This paper proposes an approach on how AR based on Marker Technology simulates the harmful effects of smoking and its consequences using Unity 3D game engine. The study also illustrates the impact of AR technology on students for better learning. AR technology can be used as a method to improve learning.

Keywords: augmented reality, marker technology, multi-platform, virtual buttons

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Authors: Faisal Nouroz, Mukaramin Mukaramin

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Of the transposable elements (TEs), the retrotransposons are the most copious elements identified from many sequenced genomes. They have played a major role in genome evolution, rearrangement, and expansions based on their copy and paste mode of proliferation. They are further divided into LTR and Non-LTR retrotransposons. The purpose of the current study was to identify the LTR REs in sequenced Phoenix dactylifera genome and to study their structural diversity. A total of 150 P. dactylifera BAC sequences with > 60kb sizes were randomly retrieved from National Center for Biotechnology Information (NCBI) database and screened for the presence of LTR retrotransposons. Seven bacterial artificial chromosomes (BAC) sequences showed full-length LTR Retrotransposons with 4 Copia and 3 Gypsy families having variable copy numbers in respective families. Reverse transcriptase (RT) domain was found as the most conserved domain among Copia and Gypsy superfamilies and was used to deduce evolutionary analysis. The amino acid residues among various RT sequences showed variability in their percentages indicating post divergence evolution. Amino acid Leucine was found in highest proportions followed by Lysine, while Methionine and Tryptophan were in lowest percentages. The phylogenetic analysis based on RT domains confirmed that although having most conserved RT regions, several evolutionary events occurred causing nucleotide polymorphisms and hence clustering of Gypsy and Copia superfamilies into their respective lineages. The study will be helpful in identification and annotation of these elements in other species and genera and their distribution patterns on chromosomes by fluorescent in situ hybridization techniques.

Keywords: transposable elements, Phoenix dactylifera, retrotransposons, phylogenetic analysis

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Authors: Kim Dongwon, Yu Songjin

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This study identifies the business value of VOC (Voice of Customer) on the business. Precisely, we intend to demonstrate how much negative and positive sentiment of VOC has an influence on car sales market share in the unites states. We extract 7 emotions such as sadness, shame, anger, fear, frustration, delight and satisfaction from the VOC data, 23,204 pieces of opinions, that had been posted on car-related on-line community from 2007 to 2009(a part of data collection from 2007 to 2015), and intend to clarify the correlation between negative and positive sentimental keywords and contribution to market share. In order to develop a lexicon for each category of negative and positive sentiment, we took advantage of Corpus program, Antconc 3.4.1.w and on-line sentimental data, SentiWordNet and identified the part of speech(POS) information of words in the customers' opinion by using a part-of-speech tagging function provided by TextAnalysisOnline. For the purpose of this present study, a total of 45,741 pieces of customers' opinions of 28 car manufacturing companies had been collected including titles and status information. We conducted an experiment to examine whether the inclusion, frequency and intensity of terms with negative and positive emotions in each category affect the adoption of customer opinions for vehicle organizations' market share. In the experiment, we statistically verified that there is correlation between customer ideas containing negative and positive emotions and variation of marker share. Particularly, "Anger," a domain of negative domains, is significantly influential to car sales market share. The domain "Delight" and "Satisfaction" increased in proportion to growth of market share.

Keywords: data mining, opinion mining, sentiment analysis, VOC

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Authors: Sara Przetocka, Krzysztof Żak, Grzegorz Dubin, Tadeusz Holak

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Toll-like receptors (TLRs) play central role in the innate immune response and inflammation by recognizing pathogen-associated molecular patterns (PAMPs). A fundamental basis of TLR signalling is dependent upon the recruitment and association of adaptor molecules that contain the structurally conserved Toll/interleukin-1 receptor (TIR) domain. MyD88 (myeloid differentiation primary response gene 88) is the universal adaptor for TLRs and cooperates with Mal (MyD88 adapter-like protein, also known as TIRAP) in TLR4 response which is predominantly used in inflammation, host defence and carcinogenesis. Up to date two possible models of MyD88, Mal and TLR4 interactions have been proposed. The aim of our studies is to confirm or abolish presented models and accomplish the full structural characterisation of TIR domains interaction. Using molecular cloning methods we obtained several construct of MyD88 and Mal TIR domain with GST or 6xHis tag. Gel filtration method as well as pull-down analysis confirmed that recombinant TIR domains from MyD88 and Mal are binding in complexes. To examine whether obtained complexes are homo- or heterodimers we carried out cross-linking reaction of TIR domains with BS3 compound combined with mass spectrometry. To investigate which amino acid residues are involved in this interaction the NMR titration experiments were performed. 15N MyD88-TIR solution was complemented with non-labelled Mal-TIR. The results undoubtedly indicate that MyD88-TIR interact with Mal-TIR. Moreover 2D spectra demonstrated that simultaneously Mal-TIR self-dimerization occurs which is necessary to create proper scaffold for Mal-TIR and MyD88-TIR interaction. Final step of this study will be crystallization of MyD88 and Mal TIR domains complex. This crystal structure and characterisation of its interface will have an impact in understanding the TLR signalling pathway and possibly will be used in development of new anti-cancer treatment.

Keywords: cancer, MyD88, TIR domains, Toll-like receptors

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Authors: Sung-Hyeon Park, Jin-Wook Jang, Hak-Sung Kim

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In recent years, Terahertz (THz) time-domain spectroscopy (TDS) imaging method has been received considerable interest as a promising non-destructive technique for detection of internal defects. In comparison to other non-destructive techniques such as x-ray inspection method, scanning acoustic tomograph (SAT) and microwave inspection method, THz-TDS imaging method has many advantages: First, it can measure the exact thickness and location of defects. Second, it doesn’t require the liquid couplant while it is very crucial to deliver that power of ultrasonic wave in SAT method. Third, it didn’t damage to materials and be harmful to human bodies while x-ray inspection method does. Finally, it exhibits better spatial resolution than microwave inspection method. However, this technology couldn’t be applied to IC package because THz radiation can penetrate through a wide variety of materials including polymers and ceramics except of metals. Therefore, it is difficult to detect the defects in IC package which are composed of not only epoxy and semiconductor materials but also various metals such as copper, aluminum and gold. In this work, we proposed a special method for detecting the void in the IC package using THz-TDS imaging system. The IC package specimens for this study are prepared by Packaging Engineering Team in Samsung Electronics. Our THz-TDS imaging system has a special reflection mode called pitch-catch mode which can change the incidence angle in the reflection mode from 10 o to 70 o while the others have transmission and the normal reflection mode or the reflection mode fixed at certain angle. Therefore, to find the voids in the IC package, we investigated the appropriate angle as changing the incidence angle of THz wave emitter and detector. As the results, the voids in the IC packages were successfully detected using our THz-TDS imaging system.

Keywords: terahertz, non-destructive technique, void, IC package

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Authors: Băilă Diana Irinel, Păcurar Răzvan, Păcurar Ancuța

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In the last years, composite materials are increasingly used in automotive, aeronautic, aerospace, construction applications. Composite materials have been used in aerospace in applications such as engine blades, brackets, interiors, nacelles, propellers/rotors, single aisle wings, wide body wings. The fields of use of composite materials have multiplied with the improvement of material properties, such as stability and adaptation to the environment, mechanical tests, wear resistance, moisture resistance, etc. The composite materials are classified concerning type of matrix materials, as metallic, polymeric and ceramic based composites and are grouped according to the reinforcement type as fibre, obtaining particulate and laminate composites. Production of a better material is made more likely by combining two or more materials with complementary properties. The best combination of strength and ductility may be accomplished in solids that consist of fibres embedded in a host material. Polyester is a suitable component for composite materials, as it adheres so readily to the particles, sheets, or fibres of the other components. The important properties of the reinforcing fibres are their high strength and high modulus of elasticity. For applications, as in automotive or in aeronautical domain, in which a high strength-to-weight ratio is important, non-metallic fibres such as fiberglass have a distinct advantage because of their low density. In general, the glass fibres content varied between 9 to 33% wt. in the composites. In this article, high-performance types of composite materials glass-epoxy and glass-polyester used in automotive domain will be analyzed, performing tensile and flexural tests and SEM analyzes.

Keywords: glass-polyester composite, glass fibre, traction and flexion tests, SEM analyzes

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Authors: Rizky Oktaviana

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The main purpose of studying lies in improving students’ understanding. Teachers usually use written test to measure students’ understanding about learning material especially mathematical learning material. This common method actually has a lack point, such that in mathematics content, written test only show procedural steps to solve mathematical problems. Therefore, teachers unable to see whether students actually understand about mathematical concepts and the relation between concepts or not. One of the best tools to observe students’ understanding about the mathematical concepts is concept map. The goal of this research is to describe junior high school students understanding about mathematical concepts through Concept Maps based on the difference of mathematical ability. There were three steps in this research; the first step was choosing the research subjects by giving mathematical ability test to students. The subjects of this research are three students with difference mathematical ability, high, intermediate and low mathematical ability. The second step was giving concept mapping training to the chosen subjects. The last step was giving concept mapping task about the function to the subjects. Nodes which are the representation of concepts of function were provided in concept mapping task. The subjects had to use the nodes in concept mapping. Based on data analysis, the result of this research shows that subject with high mathematical ability has formal understanding, due to that subject could see the connection between concepts of function and arranged the concepts become concept map with valid hierarchy. Subject with intermediate mathematical ability has relational understanding, because subject could arranged all the given concepts and gave appropriate label between concepts though it did not represent the connection specifically yet. Whereas subject with low mathematical ability has poor understanding about function, it can be seen from the concept map which is only used few of the given concepts because subject could not see the connection between concepts. All subjects have instrumental understanding for the relation between linear function concept, quadratic function concept and domain, co domain, range.

Keywords: concept map, concept mapping, mathematical concepts, understanding

Procedia PDF Downloads 258

Authors: Jérémy Philippe, Lucien Baldas, Batoul Attar, Jean-Charles Mare

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The proposed communication deals with the research and development of a rotary direct-drive servo valve for aerospace applications. A key challenge of the project is to downsize the electromagnetic torque motor by reducing the torque required to drive the rotary spool. It is intended to optimize the spool and the sleeve geometries by combining a Computational Fluid Dynamics (CFD) approach with commercial optimization software. The present communication addresses an important phase of the project, which consists firstly of gaining confidence in the simulation results. It is well known that the force needed to pilot a sliding spool valve comes from several physical effects: hydraulic forces, friction and inertia/mass of the moving assembly. Among them, the flow force is usually a major contributor to the steady-state (or Root Mean Square) driving torque. In recent decades, CFD has gradually become a standard simulation tool for studying fluid-structure interactions. However, in the particular case of high-pressure valve design, the authors have experienced that the calculated overall hydraulic force depends on the parameterization and options used to build and run the CFD model. To solve this issue, the authors have selected the standard case of the linear spool valve, which is addressed in detail in numerous scientific references (analytical models, experiments, CFD simulations). The first CFD simulations run by the authors have shown that the evolution of the equivalent discharge coefficient vs. Reynolds number at the metering orifice corresponds well to the values that can be predicted by the classical analytical models. Oppositely, the simulated flow force was found to be quite different from the value calculated analytically. This drove the authors to investigate minutely the influence of the studied domain and the setting of the CFD simulation. It was firstly shown that the flow recirculates in the inlet and outlet channels if their length is not sufficient regarding their hydraulic diameter. The dead volume on the uncontrolled orifice side also plays a significant role. These examples highlight the influence of the geometry of the fluid domain considered. The second action was to investigate the influence of the type of mesh, the turbulence models and near-wall approaches, and the numerical solver and discretization scheme order. Two approaches were used to determine the overall hydraulic force acting on the moving spool. First, the force was deduced from the momentum balance on a control domain delimited by the valve inlet and outlet and the spool walls. Second, the overall hydraulic force was calculated from the integral of pressure and shear forces acting at the boundaries of the fluid domain. This underlined the significant contribution of the viscous forces acting on the spool between the inlet and outlet orifices, which are generally not considered in the literature. This also emphasized the influence of the choices made for the implementation of CFD calculation and results analysis. With the step-by-step process adopted to increase confidence in the CFD simulations, the authors propose a set of best practices and recommendations for the efficient use of CFD to design high-pressure spool valves.

Keywords: computational fluid dynamics, hydraulic forces, servovalve, rotary servovalve

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Authors: Bahar Tunctan, Sefika Pinar Kucukkavruk, Meryem Temiz-Resitoglu, Demet Sinem Guden, Ayse Nihal Sari, Seyhan Sahan-Firat, Mahesh P. Paudyal, John R. Falck, Kafait U. Malik

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We hypothesized that 20-hydroxyeicosatetraenoic acid (20-HETE) mimetics such as N-(20-hydroxyeicosa-5[Z],14[Z]-dienoyl)glycine (5,14-HEDGE) may be beneficial for preventing mortality due to inflammation induced by lipopolysaccharide (LPS). This study aims to assess the effect of 5,14-HEDGE on the LPS-induced changes in nucleotide binding domain and leucine-rich repeat protein 3 (NLRP3)/apoptosis-associated speck-like protein containing a caspase activation and recruitment domain (ASC)/pro-caspase-1 inflammasome. Rats were injected with saline (4 ml/kg) or LPS (10 mg/kg) at time 0. Blood pressure and heart rate were measured using a tail-cuff device. 5,14-HEDGE (30 mg/kg) was administered to rats 1 h after injection of saline or LPS. The rats were sacrificed 4 h after saline or LPS injection and kidney, heart, thoracic aorta, and superior mesenteric artery were isolated for measurement of caspase-1/11 p20, NLRP3, ASC, and β-actin proteins as well as interleukin-1β (IL-1β) levels. Blood pressure decreased by 33 mmHg and heart rate increased by 63 bpm in the LPS-treated rats. In the LPS-treated rats, tissue protein expression of caspase-1/11 p20, NLRP3, and ASC in addition to IL-1β levels were increased. 5,14-HEDGE prevented the LPS-induced changes. Our findings suggest that inhibition of renal, cardiac, and vascular formation/activity of NLRP3/ASC/pro-caspase-1 inflammasome involved in the protective effect of 5,14-HEDGE on LPS-induced septic shock in rats. This work was financially supported by the Mersin University (2015-AP3-1343) and USPHS NIH (PO1 HL034300).

Keywords: 5, 14-HEDGE, lipopolysaccharide, NLRP3, inflammasome, septic shock

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Authors: Priscilla Omonedo, Paul Bocij

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Since the emergence of e-commerce, the world of business has witnessed a radical shift in the way business activities are conducted. However, the emergence of m-Commerce has further pushed the boundaries of virtual commerce revolution. As a result, there seems to be a growing blur in the distinction between e-Commerce and m-Commerce. In addition, existing definitions for both forms of commerce highlight characteristics (e.g. type of device and activity conducted) that may be applicable to both concepts. The aim of this paper is to identify the characteristics that help define and delineate between e- and m- Commerce. The paper concludes that characteristics of mobility, ubiquity, and immediacy provides a clearer and simpler template to distinguish between e-commerce and m-commerce.

Keywords: e-commerce, m-commerce, mobility, ubiquity

Procedia PDF Downloads 522

Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

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Authors: Cory B. Portner, Julie A. Grauert, Lisa M. Stromme, Shelby D. Anderson, Franji H. Mayes

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Introduction: WASHINGTON state in the Pacific Northwest of the United States is internationally known for its technology industry, fisheries, agriculture, and vistas. On January 21, 2020, Washington state also became known as the first state with a confirmed COVID-19 case in the United States, thrusting the state into the international spotlight as the world came to grips with the global threat of this disease presented. Tourism is Washington state’s fourth-largest industry. Tourism to the state generates over 1.8 billion dollars (USD) in local and state tax revenue and employs over 180,000 people. Communicating with residents, stakeholders, and visitors on the status of disease activity, prevention measures, and response updates was vital to stopping the pandemic and increasing compliance and awareness. Significance: In order to communicate vital public health updates, guidance implementation, and safety measures to the public, the Washington State Department of Health established routine live virtual media briefings to reach audiences via social media, internet television, and broadcast television. Through close partnership with regional broadcast news stations and the state public affairs news network, the Washington State Department of Health hosted 95 media briefings from January 2020 through September 2022 and continues to regularly host live virtual media briefings to accommodate the needs of the public and media. Methods: Our methods quickly evolved from hosting briefings in the cement closet of a military base to being able to produce and stream the briefings live from any home-office location. The content was tailored to the hot topic of the day and to the reporter's questions and needs. Virtual media briefings hosted through inexpensive or free platforms online are extremely cost-effective: the only mandatory components are WiFi, a laptop, and a monitor. There is no longer a need for a fancy studio or expensive production software to achieve the goal of communicating credible, reliable information promptly. With minimal investment and a small learning curve, facilitators and panelists are able to host highly produced and engaging media availabilities from their living rooms. Results: The briefings quickly developed a reputation as the best source for local and national journalists to get the latest and most factually accurate information about the pandemic. In the height of the COVID-19 response, 135 unique media outlets logged on to participate in the briefing. The briefings typically featured 4-5 panelists, with as many as 9 experts in attendance to provide information and respond to media questions. Preparation was always a priority: Public Affairs staff for the Washington State Department of Health produced over 170 presenter remarks, including guidance on talking points for 63 expert guest panelists. Implication For Practice: Information is today’s most valuable currency. The ability to disseminate correct information urgently and on a wide scale is the most effective tool in crisis communication. Due to our role as the first state with a confirmed COVID-19 case, we were forced to develop the most accurate and effective way to get life-saving information to the public. The cost-effective, web-based methods we developed can be applied in any crisis to educate and protect communities under threat, ultimately saving lives from a laptop.

Keywords: crisis communications, public relations, media management, news media

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Authors: Karima Kimouche

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In this paper, we consider the asymptotic problems in spectral analysis of stationary causal random fields. We impose conditions only involving (conditional) moments, which are easily verifiable for a variety of nonlinear random fields. Limiting distributions of periodograms and smoothed periodogram spectral density estimates are obtained and applications to the spectral domain bootstrap are given.

Keywords: spatial nonlinear processes, spectral estimators, GMC condition, bootstrap method

Procedia PDF Downloads 434

Authors: Laetitia Lemiere, Marie Gosme, Gerard Subsol, Marc Jaeger

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Agroforestry is recognized as a way of developing sustainable and resilient agriculture that can fight against climate change. However, the number of species combinations, spatial configurations, and management options for trees and crops is vast. These choices must be adapted to the pedoclimatic and socio-economic contexts and to the objectives of the farmer, who therefore needs support in designing his system. Participative design workshops are a good way to integrate the knowledge of several experts in order to design such complex systems. The design of agroforestry systems should take into account both spatial aspects (e.g., spacing of trees within the lines and between lines, tree line orientation, tree-crop distance, species spatial patterns) and temporal aspects (e.g., crop rotations, tree thinning and pruning, tree planting in the case of successional agroforestry). Furthermore, the interactions between trees and crops evolve as the trees grow. However, agroforestry design workshops generally emphasize the spatial aspect only through the use of static tokens to represent the different species when designing the spatial configuration of the system. Augmented reality (AR) may overcome this limitation, allowing to visualize dynamic representations of trees and crops, and also their interactions, while at the same time retaining the possibility to physically interact with the system being designed (i.e., move trees, add or remove species, etc.). We propose an ergonomic digital solution capable of assisting a group of agroforestry experts to design an agroforestry system and to represent it. We investigated the use of web-based marker-based AR that does not require specific hardware and does not require specific installation so that all users could use their own smartphones right out of the pocket. We developed a prototype mobilizing the AR.js, ArToolKit.js, and Three.js open source libraries. In our implementation, we gradually build a virtual agroforestry system pattern scene from the users' interactions. A specific set of markers initialize the scene properties, and the various plant species are added and located during the workshop design session. The full virtual scene, including the trees positions with their neighborhood, are saved for further uses, such as virtual, augmented instantiation in the farmer fields. The number of tree species available in the application is gradually increasing; we mobilize 3D digital models for walnut, poplar, wild cherry, and other popular species used in agroforestry systems. The prototype allows shadow computations and the representation of trees at various growth stages, as well as different tree generations, and is thus able to visualize the dynamics of the system over time. Future work will focus on i) the design of complex patterns mobilizing several tree/shrub organizations, not restricted to lines; ii) the design of interfaces related to cultural practices, such as clearing or pruning; iii) the representation of tree-crop interactions. Beside tree shade (light competition), our objective is to represent also below-ground competitions (water, nitrogen) or other variables of interest for the design of agroforestry systems (e.g., predicted crop yield).

Keywords: agroforestry system design, augmented reality, marker-based AR, participative design, web-based AR

Procedia PDF Downloads 154