Search results for: engine noise

Authors: Shubham Gogri, Lucia Florescu

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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

Procedia PDF Downloads 120

Authors: Liou Shyhnan, Chia Han Yang

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The study aims to investigate the promotion of innovation in the development of cultural and creative industries (CCI) and apply research on culture and creativity to this promotion. Using the research perspectives of culture and creativity as the starting points, this study has examined the challenges, trends, and opportunities that have emerged from the development of the CCI until the present. It is found that a definite context of cause and effect exist between them, and that a homologous theoretical basis can be used to understand and interpret them. Based on the characteristics of the aforementioned challenges and trends, this study has compiled two main theoretical systems for conducting research on culture and creativity: (i) reciprocal process between creativity and culture, and (ii) a mechanism for innovation involving multicultural convergence. Both theoretical systems were then used as the foundation to arrive at possible research propositions relating to the two developmental systems. This was respectively done through identification of the theoretical context through a literature review, and interviews and observations of actual case studies within Taiwan’s CCI. In so doing, the critical factors that can address the aforementioned challenges and trends were discovered. Our results indicated that, for reciprocal process between creativity and culture, we recognize that culture serves as creative resources in cultural and creative industries. According to shared consensus, culture provides symbolic meanings and emotional attachment for products and experiences offered by CCI. Besides, different cultures vary in their effects on creativity processes and standards, thus engendering distinctive preferences for and evaluations of the creative expressions and experiences of CCIs. In addition, we identify that creativity serves as the engine for driving the continuation and rebirth of cultures. Accounting for the core of culture, the employment of technology, design, and business facilitates the transformation and innovation mechanism for promoting culture continuity. In addition, with cultural centered, the digital technology, design thinking, and business model are critical constitutes of the innovation mechanism to promote the cultural continuity. Regarding cultural preservation and regeneration of local spaces and folk customs, we argue that the preservation and regeneration of local spaces and cultural cultures must embody the interactive experiences of present-day life. And cultural space and folk custom would regenerate with interact and experience in modern life. Regarding innovation mechanism for multicultural convergence, we propose that innovative stakeholders from different disciplines (e.g., creators, designers, engineers, and marketers) in CCIs rely on the establishment of a cocreation mechanism to promote interdisciplinary interaction. Furthermore, CCI development needs to develop a cocreation mechanism for enhancing the interdisciplinary collaboration among CCI innovation stakeholders. We further argue multicultural mixing would enhance innovation in developing CCI, and assuming an open and mutually enlightening attitude to enrich one another’s cultures in the multicultural exchanges under globalization will create diversity in homogenous CCIs. Finally, for promoting innovation in developing cultural and creative industries, we further propose a model for joint knowledge creation that can be established for enhancing the mutual reinforcement of theoretical and practical research on culture and creativity.

Keywords: culture and creativity, innovation, cultural and creative industries, cultural mixing

Procedia PDF Downloads 296

Authors: Nuzhat Sharmin

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Human being is the most integral part of the nature and responsible for maintaining ecological balance both in rural and urban areas. But unfortunately, we are not doing our job with a holistic approach. The rapid growth of urbanization is making human life more isolated from greenery. Nowadays modern urban living involves sensory deprivation and overloaded stress. In many cities and towns of the world are expanding unabated in the name of urbanization and industrialization and in fact becoming jungles of concrete. Dhaka is one of the examples of such cities where open and green spaces are decreasing because of accommodating the overflow of population. This review paper has been prepared based on interviewing 30 teenagers, both male and female in Dhaka city. There were 12 open-ended questions in the questionnaire. For the literature review information had been gathered from scholarly papers published in various peer-reviewed journals. Some information was collected from the newspapers and some from fellow colleagues working around the world. Ideally about 25% of an urban area should be kept open or with parks, fields and/or plants and vegetation. But currently Dhaka has only about 10-12% open space and these also are being filled up rapidly. Old Dhaka has only about 5% open space while the new Dhaka has about 12%. Dhaka is now one of the most populated cities in the world. Accommodating this huge influx of people Dhaka is continuously losing its open space. As a result, children and teenagers are losing their interest in playing games and making friends, rather they are mostly occupied by television, gadgets and social media. It has been known from the interview that only 28% of teenagers regularly play. But the majority of them have to play on the street and rooftop for the lack of open space. On an average they are occupied with electronic devices for 8.3 hours/day. 64% of them has chronic diseases and often visit doctors. Most shockingly 35% of them claimed for not having any friends. Green space offers relief from stress. Areas of natural environment in towns and cities are theoretically seen providing setting for recovery and recuperation from anxiety and strains of the urban environment. Good quality green spaces encourage people to walk, run, cycle and play. Green spaces improve air quality and reduce noise, while trees and shrubbery help to filter out dust and pollutants. Relaxation, contemplation and passive recreation are essential to stress management. All city governments that are losing its open spaces should immediately pay attention to this aesthetic issue for the benefit of urban people. All kinds of development must be sustainable both for human being and nature.

Keywords: greenery, health, human, urban

Procedia PDF Downloads 141

Authors: Zakia Hammouni

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Healthcare professionals’ well-being is becoming a priority during this Covid-19 pandemic due to stress, fatigue, and workload. Well before this pandemic, contemporary hospitals are endowed with environmental attributes that contribute to achieving well-being within their environment with the emphasis on the patient. The patient-centered care approach has been followed by the patient-centered design approach. Studies that have focused on the physical environment in hospitals have dealt with the patient's recovery process and his well-being. Prior scientific literature has placed less emphasis on the healthcare professionals’ interactions within the physical environment and to guide hospital designers to make evidence-based design choices to meet the needs and expectations of hospital users by considering, in addition to patients, healthcare professionals. This paper examines these issues related to the daily stress of professionals who provide care in a hospital environment. In this exploratory study, the interest was to grasp the issues related to this environment and explores the current realities of newly built hospitals based on design approaches and what attributes of the physical setting support healthcare professional’s well-being. Within a constructivist approach, this study was conducted in two care units in a new hospital in a big city in Canada before the Covid-19 pandemic (august 2nd to November 2nd 2018). A spatial evaluation of these care units allowed us to understand the interaction of health professionals in their work environment, to understand the spatial behavior of these professionals, and the narratives from 44 interviews of various healthcare professionals. The mental images validated the salient components of the hospital environment as perceived by these healthcare professionals. Thematic analysis and triangulation of the data set were conducted. Among the key attributes promoting the healthcare professionals’ well-being as revealed by the healthcare professionals are the overall light-color atmosphere in the hospital and care unit, particularly in the corridors and public areas of the hospital, the maintenance and cleanliness. The presence of the art elements also brings well-being to the health professionals as well as panoramic views from the staff lounge and corridors of the care units or elevator lobbies. Despite the overall positive assessment of this environment, some attributes need to be improved to ensure the well-being of healthcare professionals and to provide them with a restructuring environment. These are the supply of natural light, softer colors, sufficient furniture, comfortable seating in the restroom, and views, which are important in allowing these healthcare professionals to recover from their work stress. Noise is another attribute that needs to be further improved in the hospital work environment, especially in the nursing workstations and consultant's room. In conclusion, this study highlights the importance of providing healthcare professionals with work and rest areas that allow them to resist the stress they face, particularly during periods of extreme stress and fatigue such as a Covid-19 pandemic.

Keywords: healthcare facilities, healthcare professionals, physical environment, well-being

Procedia PDF Downloads 101

Authors: Irene Capecchi, Tommaso Borghini, Iacopo Bernetti

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An important tool for the enhancement of cultural sites is serious games (SG), i.e., games designed for educational purposes; SG is applied in cultural sites through trivia, puzzles, and mini-games for participation in interactive exhibitions, mobile applications, and simulations of past events. The combination of Augmented Reality (AR) and digital cultural content has also produced examples of cultural heritage recovery and revitalization around the world. Through AR, the user perceives the information of the visited place in a more real and interactive way. Another interesting technological development for the revitalization of cultural sites is the combination of AR and Global Positioning System (GPS), which integrated have the ability to enhance the user's perception of reality by providing historical and architectural information linked to specific locations organized on a route. To the author’s best knowledge, there are currently no applications that combine GPS AR and SG for cultural heritage revitalization. The present research focused on the development of an SG based on GPS and AR. The study area is the village of Caldana in Tuscany, Italy. Caldana is a fortified Renaissance village; the most important architectures are the walls, the church of San Biagio, the rectory, and the marquis' palace. The historical information is derived from extensive research by the Department of Architecture at the University of Florence. The storyboard of the SG is based on the history of the three characters who built the village: marquis Marcello Agostini, who was commissioned by Cosimo I de Medici, Grand Duke of Tuscany, to build the village, his son Ippolito and his architect Lorenzo Pomarelli. The three historical characters were modeled in 3D using the freeware MakeHuman and imported into Blender and Mixamo to associate a skeleton and blend shapes to have gestural animations and reproduce lip movement during speech. The Unity Rhubarb Lip Syncer plugin was used for the lip sync animation. The historical costumes were created by Marvelous Designer. The application was developed using the Unity 3D graphics and game engine. The AR+GPS Location plugin was used to position the 3D historical characters based on GPS coordinates. The ARFoundation library was used to display AR content. The SG is available in two versions: for children and adults. the children's version consists of finding a digital treasure consisting of valuable items and historical rarities. Players must find 9 village locations where 3D AR models of historical figures explaining the history of the village provide clues. To stimulate players, there are 3 levels of rewards for every 3 clues discovered. The rewards consist of AR masks for archaeologist, professor, and explorer. At the adult level, the SG consists of finding the 16 historical landmarks in the village, and learning historical and architectural information interactively and engagingly. The application is being tested on a sample of adults and children. Test subjects will be surveyed on a Likert scale to find out their perceptions of using the app and the learning experience between the guided tour and interaction with the app.

Keywords: augmented reality, cultural heritage, GPS, serious game

Procedia PDF Downloads 66

Authors: Guerich Mohamed, Assaf Samir

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The application of viscoelastic materials in the form of constrained layers in mechanical structures is an efficient and cost-effective technique for solving noise and vibration problems. This technique requires a design tool to select the best location, type, and thickness of the damping treatment. This paper presents a finite element model for the vibration of beams partially or fully covered with a constrained viscoelastic damping material. The model is based on Bernoulli-Euler theory for the faces and Timoshenko beam theory for the core. It uses four variables: the through-thickness constant deflection, the axial displacements of the faces, and the bending rotation of the beam. The sandwich beam finite element is compatible with the conventional C1 finite element for homogenous beams. To validate the proposed model, several free vibration analyses of fully or partially covered beams, with different locations of the damping patches and different percent coverage, are studied. The results show that the proposed approach can be used as an effective tool to study the influence of the location and treatment size on the natural frequencies and the associated modal loss factors. Then, a parametric study regarding the variation in the damping characteristics of partially covered beams has been conducted. In these studies, the effect of core shear modulus value, the effect of patch size variation, the thickness of constraining layer, and the core and the locations of the patches are considered. In partial coverage, the spatial distribution of additive damping by using viscoelastic material is as important as the thickness and material properties of the viscoelastic layer and the constraining layer. Indeed, to limit added mass and to attain maximum damping, the damping patches should be placed at optimum locations. These locations are often selected using the modal strain energy indicator. Following this approach, the damping patches are applied over regions of the base structure with the highest modal strain energy to target specific modes of vibration. In the present study, a more efficient indicator is proposed, which consists of placing the damping patches over regions of high energy dissipation through the viscoelastic layer of the fully covered sandwich beam. The presented approach is used in an optimization method to select the best location for the damping patches as well as the material thicknesses and material properties of the layers that will yield optimal damping with the minimum area of coverage.

Keywords: finite element model, damping treatment, viscoelastic materials, sandwich beam

Procedia PDF Downloads 123

Authors: Tadele Tesfaw, Ajit Pal Singh, Abebaw Mekonnen Gezahegn

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Welding is a basic manufacturing process for making components or assemblies. Recent welding economics research has focused on developing the reliable machinery database to ensure optimum production. Research on welding of materials like steel is still critical and ongoing. Welding input parameters play a very significant role in determining the quality of a weld joint. The metal active gas (MAG) welding parameters are the most important factors affecting the quality, productivity and cost of welding in many industrial operations. The aim of this study is to investigate the optimization process parameters for metal active gas welding for 60x60x5mm dead mild steel plate work-piece using Taguchi method to formulate the statistical experimental design using semi-automatic welding machine. An experimental study was conducted at Bishoftu Automotive Industry, Bishoftu, Ethiopia. This study presents the influence of four welding parameters (control factors) like welding voltage (volt), welding current (ampere), wire speed (m/min.), and gas (CO2) flow rate (lit./min.) with three different levels for variability in the welding hardness. The objective functions have been chosen in relation to parameters of MAG welding i.e., welding hardness in final products. Nine experimental runs based on an L9 orthogonal array Taguchi method were performed. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to investigate the welding characteristics of dead mild steel plate and used in order to obtain optimum levels for every input parameter at 95% confidence level. The optimal parameters setting was found is welding voltage at 22 volts, welding current at 125 ampere, wire speed at 2.15 m/min and gas flow rate at 19 l/min by using the Taguchi experimental design method within the constraints of the production process. Finally, six conformations welding have been carried out to compare the existing values; the predicated values with the experimental values confirm its effectiveness in the analysis of welding hardness (quality) in final products. It is found that welding current has a major influence on the quality of welded joints. Experimental result for optimum setting gave a better hardness of welding condition than initial setting. This study is valuable for different material and thickness variation of welding plate for Ethiopian industries.

Keywords: Weld quality, metal active gas welding, dead mild steel plate, orthogonal array, analysis of variance, Taguchi method

Procedia PDF Downloads 462

Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

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Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

Procedia PDF Downloads 48

Authors: Mishadi Herath, Amin Talei, Andreas Hermawan, Clarina Chua

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Green walls are vegetated structures on building’s wall that are considered as part of sustainable urban design. They are proved to have many micro-climate benefits such as reduction in indoor temperature, noise attenuation, and improvement in air quality. On the other hand, several studies have also been conducted on potential reuse of greywater in urban water management. Greywater is relatively clean when compared to blackwater; therefore, this study was aimed to assess the potential reuse of it for irrigating a green wall system. In this study, the campus of Monash University Malaysia located in Selangor state was considered as the study site where total 48 samples of greywater were collected from 7 toilets hand-wash and 5 pantries during 3 months period. The samples were tested to characterize the quality of greywater in the study site and compare it with local standard for irrigation water. PH and concentration of heavy metals, nutrients, Total Suspended Solids (TSS), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), total Coliform and E.coli were measured. Results showed that greywater could be directly used for irrigation with minimal treatment. Since the effluent of the system was supposed to be drained to stormwater drainage system, the effluent needed to meet certain quality requirement. Therefore, a biofiltration system was proposed to host the green wall plants and also treat the greywater (which is used as irrigation water) to the required level. To assess the performance of the proposed system, an experimental setup consisting of Polyvinyl Chloride (PVC) soil columns with sand-based filter media were prepared. Two different local creeper plants were chosen considering several factors including fast growth, low maintenance requirement, and aesthetic aspects. Three replicates of each plants were used to ensure the validity of the findings. The growth of creeping plants and their survivability was monitored for 6 months while monthly sampling and testing of effluent was conducted to evaluate effluent quality. An analysis was also conducted to estimate the potential cost and benefit of such system considering water and energy saving in the system. Results showed that the proposed system can work efficiently throughout a long period of time with minimal maintenance requirement. Moreover, the biofiltration-green wall system was found to be successful in reusing greywater as irrigating water while the effluent was meeting all the requirements for being drained to stormwater drainage system.

Keywords: biofiltration, green wall, greywater, sustainability

Procedia PDF Downloads 191

Authors: Yasser R. Tawfic, Mohamed A. Eid

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Foundation differential settlement and supported structure tilting is an occasionally occurred engineering problem. This may be caused by overloading, changes in ground soil properties or unsupported nearby excavations. Engineering thinking points directly toward the logic solution for such problem by uplifting the settled side. This can be achieved with deep foundation elements such as micro-piles and macro-piles™, jacked piers and helical piers, jet grouted soil-crete columns, compaction grout columns, cement grouting or with chemical grouting, or traditional pit underpinning with concrete and mortar. Although, some of these techniques offer economic, fast and low noise solutions, many of them are quite the contrary. For tilted structures, with limited inclination, it may be much easier to cause a balancing settlement on the less-settlement side which shall be done carefully in a proper rate. This principal has been applied in Leaning Tower of Pisa stabilization with soil extraction from the ground surface. In this research, the authors attempt to introduce a new solution with a different point of view. So, micro-tunneling technique is presented in here as an intended ground deformation cause. In general, micro-tunneling is expected to induce limited ground deformations. Thus, the researchers propose to apply the technique to form small size ground unsupported holes to produce the target deformations. This shall be done in four phases: •Application of one or more micro-tunnels, regarding the existing differential settlement value, under the raised side of the tilted structure. •For each individual tunnel, the lining shall be pulled out from both sides (from jacking and receiving shafts) in slow rate. •If required, according to calculations and site records, an additional surface load can be applied on the raised foundation side. •Finally, a strengthening soil grouting shall be applied for stabilization after adjustment. A finite element based numerical model is presented to simulate the proposed construction phases for different tunneling positions and tunnels group. For each case, the surface settlements are calculated and induced plasticity points are checked. These results show the impact of the suggested procedure on the tilted structure and its feasibility. Comparing results also show the importance of the position selection and tunnels group gradual effect. Thus, a new engineering solution is presented to one of the structural and geotechnical engineering challenges.

Keywords: differential settlement, micro-tunneling, soil-structure interaction, tilted structures

Procedia PDF Downloads 183

Authors: Nadia Belu, Laurenţiu Mihai Ionescu, Agnieszka Misztal

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The automotive industry is one of the most important industries in the world that concerns not only the economy, but also the world culture. In the present financial and economic context, this field faces new challenges posed by the current crisis, companies must maintain product quality, deliver on time and at a competitive price in order to achieve customer satisfaction. Two of the most recommended techniques of quality management by specific standards of the automotive industry, in the product development, are Failure Mode and Effects Analysis (FMEA) and Control Plan. FMEA is a methodology for risk management and quality improvement aimed at identifying potential causes of failure of products and processes, their quantification by risk assessment, ranking of the problems identified according to their importance, to the determination and implementation of corrective actions related. The companies use Control Plans realized using the results from FMEA to evaluate a process or product for strengths and weaknesses and to prevent problems before they occur. The Control Plans represent written descriptions of the systems used to control and minimize product and process variation. In addition Control Plans specify the process monitoring and control methods (for example Special Controls) used to control Special Characteristics. In this paper we propose a computer-aided solution with Genetic Algorithms in order to reduce the drafting of reports: FMEA analysis and Control Plan required in the manufacture of the product launch and improved knowledge development teams for future projects. The solution allows to the design team to introduce data entry required to FMEA. The actual analysis is performed using Genetic Algorithms to find optimum between RPN risk factor and cost of production. A feature of Genetic Algorithms is that they are used as a means of finding solutions for multi criteria optimization problems. In our case, along with three specific FMEA risk factors is considered and reduce production cost. Analysis tool will generate final reports for all FMEA processes. The data obtained in FMEA reports are automatically integrated with other entered parameters in Control Plan. Implementation of the solution is in the form of an application running in an intranet on two servers: one containing analysis and plan generation engine and the other containing the database where the initial parameters and results are stored. The results can then be used as starting solutions in the synthesis of other projects. The solution was applied to welding processes, laser cutting and bending to manufacture chassis for buses. Advantages of the solution are efficient elaboration of documents in the current project by automatically generating reports FMEA and Control Plan using multiple criteria optimization of production and build a solid knowledge base for future projects. The solution which we propose is a cheap alternative to other solutions on the market using Open Source tools in implementation.

Keywords: automotive industry, FMEA, control plan, automotive technology

Procedia PDF Downloads 380

Authors: Ahmad Haidar

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The rapid adoption of Artificial Intelligence (AI) technology holds unforeseen risks like privacy violation, unemployment, and algorithmic bias, triggering research institutions, governments, and companies to develop principles of AI ethics. The extensive and diverse literature on AI lacks an analysis of the evolution of principles developed in recent years. There are two fundamental purposes of this paper. The first is to provide insights into how the principles of AI ethics have been changed recently, including concepts like risk management and public participation. In doing so, a NOISE (Needs, Opportunities, Improvements, Strengths, & Exceptions) analysis will be presented. Second, offering a framework for building Ethical AI linked to sustainability. This research adopts an explorative approach, more specifically, an inductive approach to address the theoretical gap. Consequently, this paper tracks the different efforts to have “trustworthy AI” and “ethical AI,” concluding a list of 12 documents released from 2017 to 2022. The analysis of this list unifies the different approaches toward trustworthy AI in two steps. First, splitting the principles into two categories, technical and net benefit, and second, testing the frequency of each principle, providing the different technical principles that may be useful for stakeholders considering the lifecycle of AI, or what is known as sustainable AI. Sustainable AI is the third wave of AI ethics and a movement to drive change throughout the entire lifecycle of AI products (i.e., idea generation, training, re-tuning, implementation, and governance) in the direction of greater ecological integrity and social fairness. In this vein, results suggest transparency, privacy, fairness, safety, autonomy, and accountability as recommended technical principles to include in the lifecycle of AI. Another contribution is to capture the different basis that aid the process of AI for sustainability (e.g., towards sustainable development goals). The results indicate data governance, do no harm, human well-being, and risk management as crucial AI for sustainability principles. This study’s last contribution clarifies how the principles evolved. To illustrate, in 2018, the Montreal declaration mentioned eight principles well-being, autonomy, privacy, solidarity, democratic participation, equity, and diversity. In 2021, notions emerged from the European Commission proposal, including public trust, public participation, scientific integrity, risk assessment, flexibility, benefit and cost, and interagency coordination. The study design will strengthen the validity of previous studies. Yet, we advance knowledge in trustworthy AI by considering recent documents, linking principles with sustainable AI and AI for sustainability, and shedding light on the evolution of guidelines over time.

Keywords: artificial intelligence, AI for sustainability, declarations, framework, regulations, risks, sustainable AI

Procedia PDF Downloads 67

Authors: T. N. Goh, M. Hashmi, O. Hussain

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Temporomandibular joint (TMJ) dysfunction (TMD) is a condition that may affect patients via restricted mouth opening, significant pain during normal functioning, and/or reproducible joint noise. TMD includes myofascial pain, TMJ functional derangements (internal derangement, dislocation), and TMJ degenerative/inflammatory joint disease. Internal derangement (ID) is the most common cause of TMD-related clicking and locking. These patients are managed in a stepwise approach, from patient education (homecare advice and analgesia), splint therapy, physiotherapy, botulinum toxin treatment, to arthrocentesis. Arthrotomy is offered when the aforementioned treatment options fail to alleviate symptoms and improve quality of life. The aim of this prospective study was to review the outcomes of jaw joint open surgery in TMD patients. Patients who presented from 2015-2022 at the Oral and Maxillofacial Surgery Department in the Doncaster NHS Foundation Trust, UK, with a Wilkes classification of III -V were included. These patients underwent either i) discopexy with bone-anchoring suture (9); ii) intrapositional temporalis flap (ITF) with bone-anchoring suture (3); iii) eminoplasty and discopexy with suturing to the capsule (3); iii) discectomy + ITF with bone-anchoring suture (1); iv) discoplasty + bone-anchoring suture (1); v) ITF (1). Maximum incisal opening (MIO) was assessed pre-operatively and at each follow-up. Pain score, determined via the visual analogue scale (VAS, with 0 being no pain and 10 being the worst pain), was also recorded. A total of 18 eligible patients were identified with a mean age of 45 (range 22 - 79), of which 16 were female. The patients were scored by Wilkes Classification as III (14), IV (1), or V (4). Twelve patients had anterior disc displacement without reduction (66%) and six had degenerative/arthritic changes (33%) to the TMJ. The open joint procedure resulted in an increase in MIO and reduction in pain VAS and for the majority of patients, across all Wilkes Classifications. Pre-procedural MIO was 22.9 ± 7.4 mm and VAS was 7.8 ± 1.5. At three months post-procedure there was an increase in MIO to 34.4 ± 10.4 mm (p < 0.01) and a decrease in the VAS to 1.5 ± 2.9 (p < 0.01). Three patients were lost to follow-up prior to six months. Six were discharged at six month review and five patients were discharged at 12 months review as they were asymptomatic with good mouth opening. Four patients are still attending for annual botulinum toxin treatment. Two patients (Wilkes III and V) subsequently underwent TMJ replacement (11%). One of these patients (Wilkes III) had improvement initially to MIO of 40 mm, but subsequently relapsed to less than 20 mm due to lack of compliance with jaw rehabilitation device post-operatively. Clinical improvements in 89% of patients within the study group were found, with a return to near normal MIO range and reduced pain score. Intraoperatively, the operator found bone-anchoring suture used for discopexy/discoplasty more secure than the soft tissue anchoring suturing technique.

Keywords: bone anchoring suture, open temporomandibular joint surgery, temporomandibular joint, temporomandibular joint dysfunction

Procedia PDF Downloads 73

Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

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Authors: T. Thein, S. Kalyar Myo

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Human uses visual information for understanding the speech contents in noisy conditions or in situations where the audio signal is not available. The primary advantage of visual information is that it is not affected by the acoustic noise and cross talk among speakers. Using visual information from the lip movements can improve the accuracy and robustness of automatic speech recognition. However, a major challenge with most automatic lip reading system is to find a robust and efficient method for extracting the linguistically relevant speech information from a lip image sequence. This is a difficult task due to variation caused by different speakers, illumination, camera setting and the inherent low luminance and chrominance contrast between lip and non-lip region. Several researchers have been developing methods to overcome these problems; the one is lip reading. Moreover, it is well known that visual information about speech through lip reading is very useful for human speech recognition system. Lip reading is the technique of a comprehensive understanding of underlying speech by processing on the movement of lips. Therefore, lip reading system is one of the different supportive technologies for hearing impaired or elderly people, and it is an active research area. The need for lip reading system is ever increasing for every language. This research aims to develop a visual teaching method system for the hearing impaired persons in Myanmar, how to pronounce words precisely by identifying the features of lip movement. The proposed research will work a lip reading system for Myanmar Consonants, one syllable consonants (င (Nga)၊ ည (Nya)၊ မ (Ma)၊ လ (La)၊ ၀ (Wa)၊ သ (Tha)၊ ဟ (Ha)၊ အ (Ah) ) and two syllable consonants ( က(Ka Gyi)၊ ခ (Kha Gway)၊ ဂ (Ga Nge)၊ ဃ (Ga Gyi)၊ စ (Sa Lone)၊ ဆ (Sa Lain)၊ ဇ (Za Gwe) ၊ ဒ (Da Dway)၊ ဏ (Na Gyi)၊ န (Na Nge)၊ ပ (Pa Saug)၊ ဘ (Ba Gone)၊ ရ (Ya Gaug)၊ ဠ (La Gyi) ). In the proposed system, there are three subsystems, the first one is the lip localization system, which localizes the lips in the digital inputs. The next one is the feature extraction system, which extracts features of lip movement suitable for visual speech recognition. And the final one is the classification system. In the proposed research, Two Dimensional Discrete Cosine Transform (2D-DCT) and Linear Discriminant Analysis (LDA) with Active Contour Model (ACM) will be used for lip movement features extraction. Support Vector Machine (SVM) classifier is used for finding class parameter and class number in training set and testing set. Then, experiments will be carried out for the recognition accuracy of Myanmar consonants using the only visual information on lip movements which are useful for visual speech of Myanmar languages. The result will show the effectiveness of the lip movement recognition for Myanmar Consonants. This system will help the hearing impaired persons to use as the language learning application. This system can also be useful for normal hearing persons in noisy environments or conditions where they can find out what was said by other people without hearing voice.

Keywords: feature extraction, lip reading, lip localization, Active Contour Model (ACM), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Two Dimensional Discrete Cosine Transform (2D-DCT)

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Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

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Authors: Sun-Hee Lee, Amanda Kraley

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The “MeToo” movement is a social movement against sexual abuse and harassment. Though the hashtag went viral in 2017 following different cultural flashpoints in different countries, the initial response was quiet in South Korea. This radically changed in January 2018, when a high-ranking senior prosecutor, Seo Ji-hyun, gave a televised interview discussing being sexually assaulted by a colleague. Acknowledging public anger, particularly among women, on the long-existing problems of sexual harassment and abuse, the South Korean media have focused on several high-profile cases. Analyzing the media representation of these cases is a window into the evolving South Korean discourse around “MeToo.” This study presents a linguistic analysis of “MeToo” discourse in South Korea by utilizing a corpus-based approach. The term corpus (pl. corpora) is used to refer to electronic language data, that is, any collection of recorded instances of spoken or written language. A “MeToo” corpus has been collected by extracting newspaper articles containing the keyword “MeToo” from BIGKinds, big data analysis, and service and Nexis Uni, an online academic database search engine, to conduct this language analysis. The corpus analysis explores how Korean media represent accusers and the accused, victims and perpetrators. The extracted data includes 5,885 articles from four broadsheet newspapers (Chosun, JoongAng, Hangyore, and Kyunghyang) and 88 articles from two Korea-based English newspapers (Korea Times and Korea Herald) between January 2017 and November 2020. The information includes basic data analysis with respect to keyword frequency and network analysis and adds refined examinations of select corpus samples through naming strategies, semantic relations, and pragmatic properties. Along with the exponential increase of the number of articles containing the keyword “MeToo” from 104 articles in 2017 to 3,546 articles in 2018, the network and keyword analysis highlights ‘US,’ ‘Harvey Weinstein’, and ‘Hollywood,’ as keywords for 2017, with articles in 2018 highlighting ‘Seo Ji-Hyun, ‘politics,’ ‘President Moon,’ ‘An Ui-Jeong, ‘Lee Yoon-taek’ (the names of perpetrators), and ‘(Korean) society.’ This outcome demonstrates the shift of media focus from international affairs to domestic cases. Another crucial finding is that word ‘defamation’ is widely distributed in the “MeToo” corpus. This relates to the South Korean legal system, in which a person who defames another by publicly alleging information detrimental to their reputation—factual or fabricated—is punishable by law (Article 307 of the Criminal Act of Korea). If the defamation occurs on the internet, it is subject to aggravated punishment under the Act on Promotion of Information and Communications Network Utilization and Information Protection. These laws, in particular, have been used against accusers who have publicly come forward in the wake of “MeToo” in South Korea, adding an extra dimension of risk. This corpus analysis of “MeToo” newspaper articles contributes to the analysis of the media representation of the “MeToo” movement and sheds light on the shifting landscape of gender relations in the public sphere in South Korea.

Keywords: corpus linguistics, MeToo, newspapers, South Korea

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Authors: Richard Sogah

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The significance of transport infrastructure investments for economic growth and development has been central to the World Bank’s strategy for poverty reduction. Among the conventional surface transport infrastructures, road infrastructure is significant in facilitating the movement of human capital goods and services. When transport projects (i.e., roads, super-highways) are implemented, they come along with some negative social values (costs), such as increased noise and air pollution for local residents living near these facilities, displaced individuals, etc. However, these projects also facilitate better utilization of existing capital stock and generate other observable benefits that can be easily quantified. For example, the improvement or construction of roads creates employment, stimulates revenue generation (toll), reduces vehicle operating costs and accidents, increases accessibility, trade expansion, safety improvement, etc. Aside from these benefits, travel time savings (TTSs) which are the major economic benefits of urban and inter-urban transport projects and therefore integral in the economic assessment of transport projects, are often overlooked and omitted when estimating the benefits of transport projects, especially in developing countries. The absence of current and reliable domestic travel data and the inability of replicated models from the developed world to capture the actual value of travel time savings due to the large unemployment, underemployment, and other labor-induced distortions has contributed to the failure to assign value to travel time savings when estimating the benefits of transport schemes in developing countries. This omission of the value of travel time savings from the benefits of transport projects in developing countries poses problems for investors and stakeholders to either accept or dismiss projects based on schemes that favor reduced vehicular operating costs and other parameters rather than those that ease congestion, increase average speed, facilitate walking and handloading, and thus save travel time. Given the complex reality in the estimation of the value of travel time savings and the presence of widespread informal labour activities in Sub-Saharan Africa, we construct a “nationally ranked distribution of time values” and estimate the value of travel time savings based on the area beneath the distribution. Compared with other approaches, our method captures both formal sector workers and individuals/people who work outside the formal sector and hence changes in their time allocation occur in the informal economy and household production activities. The dataset for the estimations is sourced from the World Bank, the International Labour Organization, etc.

Keywords: road infrastructure, transport projects, travel time savings, congestion, Sub-Sahara Africa

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Authors: Edna Negron-Martinez

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Our time's global challenges and trends —like those associated with climate change, demographics displacements, growing health inequalities, and increasing burden of diseases— have complex connections to the determinants of health. Information on the burden of disease causes and prevention is fundamental for public health actions, like preparedness and responses for disasters, and recovery resources after the event. For instance, there is an increasing consensus about key findings of the effects and connections of the global burden of disease, as it generates substantial healthcare costs, consumes essential resources and prevents the attainment of optimal health and well-being. The goal of this research endeavor is to promote a comprehensive understanding of the connections between social, environmental, and economic influences on health. These connections are illustrated by pulling from clearly the core curriculum of multidisciplinary areas —as urban design, energy, housing, and economy— as well as in the health system itself. A systematic review of primary and secondary data included a variety of issues as global health, natural disasters, and critical pollution impacts on people's health and the ecosystems. Environmental health is challenged by the unsustainable consumption patterns and the resulting contaminants that abound in many cities and urban settings around the world. Poverty, inadequate housing, and poor health are usually linked. The house is a primary environmental health context for any individual and especially for more vulnerable groups; such as children, older adults and those who are sick. Nevertheless, very few countries show strong decoupling of environmental degradation from economic growth, as indicated by a recent 2017 Report of the World Bank. Worth noting, the environmental fraction of the global burden of disease in a 2016 World Health Organization (WHO) report estimated that 12.6 million global deaths, accounting for 23% (95% CI: 13-34%) of all deaths were attributable to the environment. Among the environmental contaminants include heavy metals, noise pollution, light pollution, and urban sprawl. Those key findings make a call to the significance to urgently adopt in a global scale the United Nations post-2015 Sustainable Development Goals (SDGs). The SDGs address the social, environmental, and economic factors that influence health and health inequalities, advising how these sectors, in turn, benefit from a healthy population. Consequently, more actions are necessary from an inter-sectoral and systemic paradigm to enforce an integrated sustainability policy implementation aimed at the environmental, social, and economic determinants of health.

Keywords: building capacity for workforce development, ecological and environmental health effects of pollution, public health education, sustainability

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Authors: Carolina Schencke, Cristian Sandoval, Belgica Vasquez, Mariano Del Sol

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Introduction: In a burn injury, the successful repair requires not only the participation of various cells, such as granulocytes and fibroblasts, but also of collagen, which plays a crucial role as a structural and regulatory molecule of scar tissue. Since honey and ascorbic acid have presented a great therapeutic potential to cellular and structural level, experimental studies have proposed its combination in the treatment of wounds. Aim: To evaluate stereological and morphometric parameters of healing wounds, caused by burns, treated with honey Ulmo (Eucryphia cordifolia) unsupplemented, comparing its effect with Ulmo honey supplemented with ascorbic acid. Materials and Methods: Fifteen healthy adult guinea pigs (Cavia porcellus) were used, of both sexes, average weight 450 g from the Centro de Excelencia en Estudios Morfológicos y Quirúrgicos (CEMyQ) at the Universidad de La Frontera, Chile. The animals were divided at random into three groups: positive control (C+), honey only (H) and supplemented honey (SH) and were fed on pellets supplemented with ascorbic acid and water ad libitum, under ambient conditions controlled for temperature, ambient noise and a cycle of 12h light–darkness. The protocol for the experiment was approved by the Scientific Ethics Committee of the Universidad de La Frontera, Chile. The parameters measured were number density per area (NA), volume density (VV), and surface density (SV) of fibroblast; NA and VV of polymorphonuclear cells (PMN) and, evaluation of the content of collagen fibers in the scar dermis. One-way ANOVA was used for statistics analysis and its respective Post hoc tests. Results: The ANOVA analysis for NA, VV and SV of fibroblasts, NA and VV of PMN, and evaluation of collagen content, type I and III, showed that at least one group differs from other (P≤ 0.001). There were differences (P= 0.000) in NA of fibroblast between the groups [C+= 3599.560 mm-2 (SD= 764.461), H= 3355.336 mm-2 (SD= 699.443) and SH= 4253.025 mm-2 (SD= 1041.751)]. The VV and SV of fibroblast increased (P= 0.000) in the SH group [20.400% (SD= 5.897) and 100.876 mm2/mm3 (SD= 29.431), respectively], compared to the C+ [16.324% (SD= 7.719) and 81.676 mm2/mm3 (SD= 28.884), respectively). The mean values of NA and VV of PMN were higher (P= 0.000) in the H [756.875 mm-2 (SD= 516.489) and 2.686% (SD= 2.380), respectively) group. Regarding to the evaluation of the content of collagen fibers, type I and III, the one-way analysis of ANOVA showed a statistically significant difference (P< 0.05). The content of collagen fibers type I was higher in C+ (1988.292 μm2; SD= 1312.379), while the content of collagen fibers type III was higher in SH (1967.163 μm2; SD= 1047.944 μm2) group. Conclusions: The stereological results were correlated with the stage of healing observed for each group. These results suggest that the combination of honey with ascorbic acid potentiate the healing effect, where both participated synergistically.

Keywords: ascorbic acid, morphometry, stereology, Ulmo honey

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Authors: Walter W. Loo

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China declared the “zero discharge rules which leave no toxics into our living environment and deliver blue sky, green land and clean water to many generations to come”. The achievement of ZWD will provide conservation of water, soil and energy and provide drastic increase in Gross Domestic Products (GDP). Our society’s engine needs a major tune up; it is sputtering. ZWD is achieved in world’s space stations – no toxic air emission and the water is totally recycled and solid wastes all come back to earth. This is all done with solar power. These are all achieved under extreme temperature, pressure and zero gravity in space. ZWD can be achieved on earth under much less fluctuations in temperature, pressure and normal gravity environment. ZWD systems are not expensive and will have multiple beneficial returns on investment which are both financially and environmentally acceptable. The paper will include successful case histories since the mid-1970s. ZWD discharge can be applied to the following types of projects: nuclear and coal fire power plants with a closed loop system that will eliminate thermal water discharge; residential communities with wastewater treatment sump and recycle the water use as a secondary water supply; waste water treatment Plants with complete water recycling including water distillation to produce distilled water by very economical 24-hours solar power plant. Landfill remediation is based on neutralization of landfilled gas odor and preventing anaerobic leachate formation. It is an aerobic condition which will render landfill gas emission explosion proof. Desert development is the development of recovering soil moisture from soil and completing a closed loop water cycle by solar energy within and underneath an enclosed greenhouse. Salt-alkali land development can be achieved by solar distillation of salty shallow water into distilled water. The distilled water can be used for soil washing and irrigation and complete a closed loop water cycle with energy and water conservation. Heavy metals remediation can be achieved by precipitation of dissolved toxic metals below the plant or vegetation root zone by solar electricity without pumping and treating. Soil and groundwater remediation - abandoned refineries, chemical and pesticide factories can be remediated by in-situ electrobiochemical and bioventing treatment method without pumping or excavation. Toxic organic chemicals are oxidized into carbon dioxide and heavy metals precipitated below plant and vegetation root zone. New water sources: low temperature distilled water can be recycled for repeated use within a greenhouse environment by solar distillation; nano bubble water can be made from the distilled water with nano bubbles of oxygen, nitrogen and carbon dioxide from air (fertilizer water) and also eliminate the use of pesticides because the nano oxygen will break the insect growth chain in the larvae state. Three dimensional high yield greenhouses can be constructed by complete water recycling using the vadose zone soil as a filter with no farming wastewater discharge.

Keywords: greenhouses, no discharge, remediation of soil and water, wastewater

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Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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Authors: Norazlan Mohmad Misnan, Maizatul Hasyima Omar, Mohd Isa Wasiman

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Papaya (Carica papaya L., Caricaceae) is a tree which mainly cultivated for its fruits in many tropical regions including Australia, Brazil, China, Hawaii, and Malaysia. Beside of fruits, its leaves, seeds, and latex have also been traditionally used for treating diseases, which also reported to possess anti-cancer and anti- malaria properties. Its leaves have been reported to consist of various chemical compounds such as alkaloids, flavonoids and phenolics. Clitorin and manghaslin are among major flavonoids presence. Thus, the aim of this study is to quantify the purity of these isolated compounds (clitorin and manghsalin) by using quantitative Nuclear Magnetic Resonance (qNMR) analysis. Only fresh C. papaya leaves were used for juice extraction procedure and subsequently was freeze-dried to obtain a dark green powdered form of the extract prior to Centrifugal Partition Chromatography (CPC) separation. The CPC experiments were performed using a two-phase solvent system comprising ethyl acetate/butanol/water (1:4:5, v/v/v/v) solvent. The upper organic phase was used as the stationary phase, and the lower aqueous phase was employed as the mobile phase. Ten fractions were obtained after an hour runtime analysis. Fraction 6 and fraction 8 has been identified as clitorin (m/z 739.21 [M-H]-) and manghaslin (m/z 755.21 [M-H]-), respectively, based on LCMS data and full analysis of NMR (1H NMR, 13C NMR, HMBC, and HSQC). The 1H-qNMR measurements were carried out using a 400 MHz NMR spectrometer (JEOL ECS 400MHz, Japan) and deuterated methanol was used as a solvent. Quantification was performed using the AQARI method (Accurate Quantitative NMR) with deuterated 1,4-Bis(trimethylsilyl)benzene (BTMSB) as an internal reference substances. This AQARI protocol includes not only NMR measurement but also sample preparation that provide highest precision and accuracy than other qNMR methods. The 90° pulse length and the T1 relaxation times for compounds and BTMSB were determined prior to the quantification to give the best signal-to-noise ratio. Regions containing the two downfield signals from aromatic part (6.00–6.89 ppm), and the singlet signal, (18H) arising from BTMSB (0.63-1.05ppm) were selected for integration. The purity of clitorin and manghaslin were calculated to be 52.22% and 43.36%, respectively. Further purification is needed in order to increase its purity. This finding has demonstrated the use of qNMR for quality control and standardization of various plant extracts and which can be applied for NMR fingerprinting of other plant-based products with good reproducibility and in the case where commercial standards is not readily available.

Keywords: Carica papaya, clitorin, manghaslin, quantitative Nuclear Magnetic Resonance, Centrifugal Partition Chromatography

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Authors: Dino Carpentras, Paul Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is dedicated to modeling the dynamic evolution of people's opinions. Models in this field are based on a micro-dynamic rule, which determines how people update their opinion when interacting. Despite the high number of new models (many of them based on new rules), little research has been dedicated to experimentally validate the rule. A few studies started bridging this literature gap by experimentally testing the rule. However, in these studies, participants are forced to express their opinion as a number instead of using natural language. Furthermore, some of these studies average data from experimental questions, without testing if differences existed between them. Indeed, it is possible that different topics could show different dynamics. For example, people may be more prone to accepting someone's else opinion regarding less polarized topics. In this work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions using natural language ('agree' or 'disagree') and the certainty of their answer, expressed as a number between 1 and 10. To keep the interaction based on natural language, certainty was not shown to other participants. We then showed to the participant someone else's opinion on the same topic and, after a distraction task, we repeated the measurement. To produce data compatible with standard opinion dynamics models, we multiplied the opinion (encoded as agree=1 and disagree=-1) with the certainty to obtain a single 'continuous opinion' ranging from -10 to 10. By analyzing the topics independently, we observed that each one shows a different initial distribution. However, the dynamics (i.e., the properties of the opinion change) appear to be similar between all topics. This suggested that the same micro-dynamic rule could be applied to unpolarized topics. Another important result is that participants that change opinion tend to maintain similar levels of certainty. This is in contrast with typical micro-dynamics rules, where agents move to an average point instead of directly jumping to the opposite continuous opinion. As expected, in the data, we also observed the effect of social influence. This means that exposing someone with 'agree' or 'disagree' influenced participants to respectively higher or lower values of the continuous opinion. However, we also observed random variations whose effect was stronger than the social influence’s one. We even observed cases of people that changed from 'agree' to 'disagree,' even if they were exposed to 'agree.' This phenomenon is surprising, as, in the standard literature, the strength of the noise is usually smaller than the strength of social influence. Finally, we also built an opinion dynamics model from the data. The model was able to explain more than 80% of the data variance. Furthermore, by iterating the model, we were able to produce polarized states even starting from an unpolarized population. This experimental approach offers a way to test the micro-dynamic rule. This also allows us to build models which are directly grounded on experimental results.

Keywords: experimental validation, micro-dynamic rule, opinion dynamics, update rule

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Authors: Lalit Ahuja, Nancy Das, Yashas Shetty

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LED lighting has been increasingly adopted for vehicles in both domestic and foreign automotive markets. Although this miniaturized technology gives the best light output, low energy consumption, and cost-efficient solutions for driving, the same is the need of the hour. In this paper, we present a methodology for driving the highest class two-wheeler headlamp with regulator and rectifier (RR) output. Unlike usual LED headlamps, which are driven by a battery, regulator, and rectifier (RR) driven, a low-cost and highly efficient LED Driver Module (LDM) is proposed. The positive half of magneto output is regulated and used to charge batteries used for various peripherals. While conventionally, the negative half was used for operating bulb-based exterior lamps. But with advancements in LED-based headlamps, which are driven by a battery, this negative half pulse remained unused in most of the vehicles. Our system uses negative half-wave rectified DC output from RR to provide constant light output at all RPMs of the vehicle. With the negative rectified DC output of RR, we have the advantage of pulsating DC input which periodically goes to zero, thus helping us to generate a constant DC output equivalent to the required LED load, and with a change in RPM, additional active thermal bypass circuit help us to maintain the efficiency and thermal rise. The methodology uses the negative half wave output of the RR along with a linear constant current driver with significantly higher efficiency. Although RR output has varied frequency and duty cycles at different engine RPMs, the driver is designed such that it provides constant current to LEDs with minimal ripple. In LED Headlamps, a DC-DC switching regulator is usually used, which is usually bulky. But with linear regulators, we’re eliminating bulky components and improving the form factor. Hence, this is both cost-efficient and compact. Presently, output ripple-free amplitude drivers with fewer components and less complexity are limited to lower-power LED Lamps. The focus of current high-efficiency research is often on high LED power applications. This paper presents a method of driving LED load at both High Beam and Low Beam using the negative half wave rectified pulsating DC from RR with minimum components, maintaining high efficiency within the thermal limitations. Linear regulators are significantly inefficient, with efficiencies typically about 40% and reaching as low as 14%. This leads to poor thermal performance. Although they don’t require complex and bulky circuitry, powering high-power devices is difficult to realise with the same. But with the input being negative half wave rectified pulsating DC, this efficiency can be improved as this helps us to generate constant DC output equivalent to LED load minimising the voltage drop on the linear regulator. Hence, losses are significantly reduced, and efficiency as high as 75% is achieved. With a change in RPM, DC voltage increases, which can be managed by active thermal bypass circuitry, thus resulting in better thermal performance. Hence, the use of bulky and expensive heat sinks can be avoided. Hence, the methodology to utilize the unused negative pulsating DC output of RR to optimize the utilization of RR output power and provide a cost-efficient solution as compared to costly DC-DC drivers.

Keywords: class D LED headlamp, regulator and rectifier, pulsating DC, low cost and highly efficient, LED driver module

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Authors: Soo-Yong Cho, Chong-Hyun Cho, Chae-Whan Rim, Sang-Kyu Choi, Jin-Gyun Kim, Ju-Seok Nam

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Recently, vertical axis wind turbines (VAWT) have been widely used to produce electricity even in urban. They have several merits such as low sound noise, easy installation of the generator and simple structure without yaw-control mechanism and so on. However, their blades are operated under the influence of the trailing vortices generated by the preceding blades. This phenomenon deteriorates its output power and makes difficulty predicting correctly its performance. In order to improve the performance of VAWT, wind power towers can be applied. Usually, the wind power tower can be constructed as a multi-story building to increase the frontal area of the wind stream. Hence, multiple sets of the VAWT can be installed within the wind power tower, and they can be operated at high elevation. Many different types of wind power tower can be used in the field. In this study, a wind power tower with circular column shape was applied, and the VAWT was installed at the center of the wind power tower. Seven guide walls were used as a strut between the floors of the wind power tower. These guide walls were utilized not only to increase the wind velocity within the wind power tower but also to adjust the wind direction for making a better working condition on the VAWT. Hence, some important design variables, such as the distance between the wind turbine and the guide wall, the outer diameter of the wind power tower, the direction of the guide wall against the wind direction, should be considered to enhance the output power on the VAWT. A numerical analysis was conducted to find the optimum dimension on design variables by using the computational fluid dynamics (CFD) among many prediction methods. The CFD could be an accurate prediction method compared with the stream-tube methods. In order to obtain the accurate results in the CFD, it needs the transient analysis and the full three-dimensional (3-D) computation. However, this full 3-D CFD could be hard to be a practical tool because it requires huge computation time. Therefore, the reduced computational domain is applied as a practical method. In this study, the computations were conducted in the reduced computational domain and they were compared with the experimental results in the literature. It was examined the mechanism of the difference between the experimental results and the computational results. The computed results showed this computational method could be an effective method in the design methodology using the optimization algorithm. After validation of the numerical method, the CFD on the wind power tower was conducted with the important design variables affecting the performance of VAWT. The results showed that the output power of the VAWT obtained using the wind power tower was increased compared to them obtained without the wind power tower. In addition, they showed that the increased output power on the wind turbine depended greatly on the dimension of the guide wall.

Keywords: CFD, performance, VAWT, wind power tower

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Authors: Morteza Ghourchi, Meraj Jafari, Atena Soheilazizi

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Today, with the globalization of communications and the connection of countries within the framework of the global economy, free zones play the most important role as the engine of global economic development and globalization of countries. In this regard, corridors have a fundamental role in linking countries and free zones physically with each other. One of these corridors is the New Silk Road corridor (One Belt, One Road initiative), which is being built by China to connect with European countries. In connecting this corridor to European countries, Iran and Turkey are among the countries that play an important role in linking China to European countries through this corridor. The New Silk Road corridor, by connecting Iran’s free zones (Sarakhs and Maku) and Turkey’s free zones (Anatolia and Europe), can provide the best opportunity for expanding economic cooperation and regional development between Iran and Turkey. It can also provide economic links between Iran and Turkey with Central Asian countries and especially the port of Khorgos. On the other hand, it can expand Iran-Turkey economic relations more than ever before with Europe in a vast economic network. The research method was descriptive-analytical, using library resources, documents of Iranian free zones, and the Internet. In an interview with Fars News Agency, Mohammad Reza Kalaei, CEO of Sarakhs Free Zone, said that the main goal of Sarakhs Special Economic Zone is to connect Iran with the Middle East and create a transit corridor towards East Asian countries, including Turkey. Also, according to an interview with Hussein Gharousi, CEO of Maku Free Zone, the importance of this region is due to the fact that Maku Free Zone, due to its geographical location and its position on the China-Europe trade route, the East-West corridor, which is the closest point to the European Union through railway and transit routes, and also due to its proximity to Eurasian countries, is an ideal opportunity for industrial and technological companies. Creating a transit corridor towards East Asian countries, including Turkey, is one of the goals of this project Free zones between Iran and Turkey can sign an agreement within the framework of the New Silk Road to expand joint investments and economic cooperation towards regional convergence. The purpose of this research is to develop economic links between Iranian and Turkish free zones along the New Silk Road, which will lead to the expansion and development of regional cooperation between the two countries within the framework of neighboring policies. The findings of this research include the development of economic diplomacy between the Secretariat of the Supreme Council of Free Zones of Iran and the General Directorate of Free Zones of Turkey, the agreement to expand cooperation between the free zones of Sarakhs, Maku, Anatolia, and Europe, holding biennial conferences between Iranian free zones along the New Silk Road with Turkish free zones, creating a joint investment fund between Iran and Turkey in the field of developing free zones along the Silk Road, helping to attract tourism between Iranian and Turkish free zones located along the New Silk Road, improving transit infrastructure and transportation to better connect Iranian free zones to Turkish free zones, communicating with China, and creating joint collaborations between China’s dry ports and its free zones with Iranian and Turkish free zones.

Keywords: network economy, new silk road (one belt, one road initiative), free zones (Sarakhs, Maku, Anatolia, Europe), regional development, neighborhood policies

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Authors: Alejandra Torres-Landa López

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Introduction: Can architecture students be creative in spaces conformed by an educational infrastructure build with paradigms of the past?, this question and others related are answered in this paper as it presents the PhD research: An anthropic conflict in Mexican Higher Education Institutes, problems and challenges of the educational infrastructure in teaching and learning History of Architecture. This research was finished in 2013 and is one of the first studies conducted nationwide in Mexico that analysis the educational infrastructure impact in learning architecture; its objective was to identify which elements of the educational infrastructure of Mexican Higher Education Institutes where architects are formed, hinder or contribute to the teaching and learning of History of Architecture; how and why it happens. The methodology: A mixed methodology was used combining quantitative and qualitative analysis. Different resources and strategies for data collection were used, such as questionnaires for students and teachers, interviews to architecture research experts, direct observations in Architecture classes, among others; the data collected was analyses using SPSS and MAXQDA. The veracity of the quantitative data was supported by the Cronbach’s Alpha Coefficient, obtaining a 0.86, figure that gives the data enough support. All the above enabled to certify the anthropic conflict in which Mexican Universities are. Major findings of the study: Although some of findings were probably not unknown, they haven’t been systematized and analyzed with the depth to which it’s done in this research. So, it can be said, that the educational infrastructure of most of the Higher Education Institutes studied, is a barrier to the educational process, some of the reasons are: the little morphological variation of space, the inadequate control of lighting, noise, temperature, equipment and furniture, the poor or none accessibility for disable people; as well as the absence, obsolescence and / or insufficiency of information technologies are some of the issues that generate an anthropic conflict understanding it as the trouble that teachers and students have to relate between them, in order to achieve significant learning). It is clear that most of the educational infrastructure of Mexican Higher Education Institutes is anchored to paradigms of the past; it seems that they respond to the previous era of industrialization. The results confirm that the educational infrastructure of Mexican Higher Education Institutes where architects are formed, is perceived as a "closed container" of people and data; infrastructure that becomes a barrier to teaching and learning process. Conclusion: The research results show it's time to change the paradigm in which we conceive the educational infrastructure, it’s time to stop seen it just only as classrooms, workshops, laboratories and libraries, as it must be seen from a constructive, urban, architectural and human point of view, taking into account their different dimensions: physical, technological, documental, social, among others; so the educational infrastructure can become a set of elements that organize and create spaces where ideas and thoughts can be shared; to be a social catalyst where people can interact between each other and with the space itself.

Keywords: educational infrastructure, impact of space in learning architecture outcomes, learning environments, teaching architecture, learning architecture

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Authors: Murray David Schane

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Though years of clinical encounters with patients with autism spectrum disorders and those with a schizoid personality the many defining diagnostic features shared between these conditions have been explored and current neurobiological differences have been reviewed; and, critical and different treatment strategies for each have been devised. The paper compares and contrasts the apparent similarities between autism spectrum disorders and the schizoid personality are found in these DSM descriptive categories: restricted range of social-emotional reciprocity; poor non-verbal communicative behavior in social interactions; difficulty developing and maintaining relationships; detachment from social relationships; lack of the desire for or enjoyment of close relationships; and preference for solitary activities. In this paper autism, fundamentally a communicative disorder, is revealed to present clinically as a pervasive aversive response to efforts to engage with or be engaged by others. Autists with the Asperger presentation typically have language but have difficulty understanding humor, irony, sarcasm, metaphoric speech, and even narratives about social relationships. They also tend to seek sameness, possibly to avoid problems of social interpretation. Repetitive behaviors engage many autists as a screen against ambient noise, social activity, and challenging interactions. Also in this paper, the schizoid personality is revealed as a pattern of social avoidance, self-sufficiency and apparent indifference to others as a complex psychological defense against a deep, long-abiding fear of appropriation and perverse manipulation. Neither genetic nor MRI studies have yet located the explanatory data that identifies the cause or the neurobiology of autism. Similarly, studies of the schizoid have yet to group that condition with those found in schizophrenia. Through presentations of clinical examples, the treatment of autists of the Asperger type is revealed to address the autist’s extreme social aversion which also precludes the experience of empathy. Autists will be revealed as forming social attachments but without the capacity to interact with mutual concern. Empathy will be shown be teachable and, as social avoidance relents, understanding of the meaning and signs of empathic needs that autists can recognize and acknowledge. Treatment of schizoids will be shown to revolve around joining empathically with the schizoid’s apprehensions about interpersonal, interactive proximity. Models of both autism and schizoid personality traits have yet to be replicated in animals, thereby eliminating the role of translational research in providing the kind of clues to behavioral patterns that can be related to genetic, epigenetic and neurobiological measures. But as these clinical examples will attest, treatment strategies have significant impact.

Keywords: autism spectrum, schizoid personality traits, neurobiological implications, critical diagnostic distinctions

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Authors: Juan Pablo Bertuzzi, Mauro Chiarella

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Employing a communication studies perspective and a socio-technological approach, this paper introduces a theoretical framework for understanding the concept of hybrid world; the avatarization phenomena; and the communicational archetype of co-hybridization. This analysis intends to make a contribution to future design of virtual reality experimental applications. Ultimately, this paper presents an ongoing research project that proposes the study of human-avatar interactions in digital educational environments, as well as an innovative reflection on inner digital communication. The aforementioned project presents the analysis of human-avatar interactions, through the development of an interactive experience in virtual reality. The goal is to generate an innovative communicational dimension that could reinforce the hypotheses presented throughout this paper. Being thought for its initial application in educational environments, the analysis and results of this research are dependent and have been prepared in regard of a meticulous planning of: the conception of a 3D digital platform; the interactive game objects; the AI or computer avatars; the human representation as hybrid avatars; and lastly, the potential of immersion, ergonomics and control diversity that can provide the virtual reality system and the game engine that were chosen. The project is divided in two main axes: The first part is the structural one, as it is mandatory for the construction of an original prototype. The 3D model is inspired by the physical space that belongs to an academic institution. The incorporation of smart objects, avatars, game mechanics, game objects, and a dialogue system will be part of the prototype. These elements have all the objective of gamifying the educational environment. To generate a continuous participation and a large amount of interactions, the digital world will be navigable both, in a conventional device and in a virtual reality system. This decision is made, practically, to facilitate the communication between students and teachers; and strategically, because it will help to a faster population of the digital environment. The second part is concentrated to content production and further data analysis. The challenge is to offer a scenario’s diversity that compels users to interact and to question their digital embodiment. The multipath narrative content that is being applied is focused on the subjects covered in this paper. Furthermore, the experience with virtual reality devices proposes users to experiment in a mixture of a seemingly infinite digital world and a small physical area of movement. This combination will lead the narrative content and it will be crucial in order to restrict user’s interactions. The main point is to stimulate and to grow in the user the need of his hybrid avatar’s help. By building an inner communication between user’s physicality and user’s digital extension, the interactions will serve as a self-guide through the gameworld. This is the first attempt to make explicit the avatarization phenomena and to further analyze the communicational archetype of co-hybridization. The challenge of the upcoming years will be to take advantage from these forms of generalized avatarization, in order to create awareness and establish innovative forms of hybridization.

Keywords: avatar, hybrid worlds, socio-technology, virtual reality

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