Search results for: educational techniques
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9678

Search results for: educational techniques

348 Empowering Indigenous Epistemologies in Geothermal Development

Authors: Te Kīpa Kēpa B. Morgan, Oliver W. Mcmillan, Dylan N. Taute, Tumanako N. Fa'aui

Abstract:

Epistemologies are ways of knowing. Indigenous Peoples are aware that they do not perceive and experience the world in the same way as others. So it is important when empowering Indigenous epistemologies, such as that of the New Zealand Māori, to also be able to represent a scientific understanding within the same analysis. A geothermal development assessment tool has been developed by adapting the Mauri Model Decision Making Framework. Mauri is a metric that is capable of representing the change in the life-supporting capacity of things and collections of things. The Mauri Model is a method of grouping mauri indicators as dimension averages in order to allow holistic assessment and also to conduct sensitivity analyses for the effect of worldview bias. R-shiny is the coding platform used for this Vision Mātauranga research which has created an expert decision support tool (DST) that combines a stakeholder assessment of worldview bias with an impact assessment of mauri-based indicators to determine the sustainability of proposed geothermal development. The initial intention was to develop guidelines for quantifying mātauranga Māori impacts related to geothermal resources. To do this, three typical scenarios were considered: a resource owner wishing to assess the potential for new geothermal development; another party wishing to assess the environmental and cultural impacts of the proposed development; an assessment that focuses on the holistic sustainability of the resource, including its surface features. Indicator sets and measurement thresholds were developed that are considered necessary considerations for each assessment context and these have been grouped to represent four mauri dimensions that mirror the four well-being criteria used for resource management in Aotearoa, New Zealand. Two case studies have been conducted to test the DST suitability for quantifying mātauranga Māori and other biophysical factors related to a geothermal system. This involved estimating mauri0meter values for physical features such as temperature, flow rate, frequency, colour, and developing indicators to also quantify qualitative observations about the geothermal system made by Māori. A retrospective analysis has then been conducted to verify different understandings of the geothermal system. The case studies found that the expert DST is useful for geothermal development assessment, especially where hapū (indigenous sub-tribal grouping) are conflicted regarding the benefits and disadvantages of their’ and others’ geothermal developments. These results have been supplemented with evaluations for the cumulative impacts of geothermal developments experienced by different parties using integration techniques applied to the time history curve of the expert DST worldview bias weighted plotted against the mauri0meter score. Cumulative impacts represent the change in resilience or potential of geothermal systems, which directly assists with the holistic interpretation of change from an Indigenous Peoples’ perspective.

Keywords: decision support tool, holistic geothermal assessment, indigenous knowledge, mauri model decision-making framework

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347 Flux-Gate vs. Anisotropic Magneto Resistance Magnetic Sensors Characteristics in Closed-Loop Operation

Authors: Neoclis Hadjigeorgiou, Spyridon Angelopoulos, Evangelos V. Hristoforou, Paul P. Sotiriadis

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The increasing demand for accurate and reliable magnetic measurements over the past decades has paved the way for the development of different types of magnetic sensing systems as well as of more advanced measurement techniques. Anisotropic Magneto Resistance (AMR) sensors have emerged as a promising solution for applications requiring high resolution, providing an ideal balance between performance and cost. However, certain issues of AMR sensors such as non-linear response and measurement noise are rarely discussed in the relevant literature. In this work, an analog closed loop compensation system is proposed, developed and tested as a means to eliminate the non-linearity of AMR response, reduce the 1/f noise and enhance the sensitivity of magnetic sensor. Additional performance aspects, such as cross-axis and hysteresis effects are also examined. This system was analyzed using an analytical model and a P-Spice model, considering both the sensor itself as well as the accompanying electronic circuitry. In addition, a commercial closed loop architecture Flux-Gate sensor (calibrated and certified), has been used for comparison purposes. Three different experimental setups have been constructed for the purposes of this work, each one utilized for DC magnetic field measurements, AC magnetic field measurements and Noise density measurements respectively. The DC magnetic field measurements have been conducted in laboratory environment employing a cubic Helmholtz coil setup in order to calibrate and characterize the system under consideration. A high-accuracy DC power supply has been used for providing the operating current to the Helmholtz coils. The results were recorded by a multichannel voltmeter The AC magnetic field measurements have been conducted in laboratory environment employing a cubic Helmholtz coil setup in order to examine the effective bandwidth not only of the proposed system but also for the Flux-Gate sensor. A voltage controlled current source driven by a function generator has been utilized for the Helmholtz coil excitation. The result was observed by the oscilloscope. The third experimental apparatus incorporated an AC magnetic shielding construction composed of several layers of electric steel that had been demagnetized prior to the experimental process. Each sensor was placed alone and the response was captured by the oscilloscope. The preliminary experimental results indicate that closed loop AMR response presented a maximum deviation of 0.36% with respect to the ideal linear response, while the corresponding values for the open loop AMR system and the Fluxgate sensor reached 2% and 0.01% respectively. Moreover, the noise density of the proposed close loop AMR sensor system remained almost as low as the noise density of the AMR sensor itself, yet considerably higher than that of the Flux-Gate sensor. All relevant numerical data are presented in the paper.

Keywords: AMR sensor, chopper, closed loop, electronic noise, magnetic noise, memory effects, flux-gate sensor, linearity improvement, sensitivity improvement

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346 Hybridization of Mathematical Transforms for Robust Video Watermarking Technique

Authors: Harpal Singh, Sakshi Batra

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The widespread and easy accesses to multimedia contents and possibility to make numerous copies without loss of significant fidelity have roused the requirement of digital rights management. Thus this problem can be effectively solved by Digital watermarking technology. This is a concept of embedding some sort of data or special pattern (watermark) in the multimedia content; this information will later prove ownership in case of a dispute, trace the marked document’s dissemination, identify a misappropriating person or simply inform user about the rights-holder. The primary motive of digital watermarking is to embed the data imperceptibly and robustly in the host information. Extensive counts of watermarking techniques have been developed to embed copyright marks or data in digital images, video, audio and other multimedia objects. With the development of digital video-based innovations, copyright dilemma for the multimedia industry increases. Video watermarking had been proposed in recent years to serve the issue of illicit copying and allocation of videos. It is the process of embedding copyright information in video bit streams. Practically video watermarking schemes have to address some serious challenges as compared to image watermarking schemes like real-time requirements in the video broadcasting, large volume of inherently redundant data between frames, the unbalance between the motion and motionless regions etc. and they are particularly vulnerable to attacks, for example, frame swapping, statistical analysis, rotation, noise, median and crop attacks. In this paper, an effective, robust and imperceptible video watermarking algorithm is proposed based on hybridization of powerful mathematical transforms; Fractional Fourier Transform (FrFT), Discrete Wavelet transforms (DWT) and Singular Value Decomposition (SVD) using redundant wavelet. This scheme utilizes various transforms for embedding watermarks on different layers by using Hybrid systems. For this purpose, the video frames are portioned into layers (RGB) and the watermark is being embedded in two forms in the video frames using SVD portioning of the watermark, and DWT sub-band decomposition of host video, to facilitate copyright safeguard as well as reliability. The FrFT orders are used as the encryption key that allows the watermarking method to be more robust against various attacks. The fidelity of the scheme is enhanced by introducing key generation and wavelet based key embedding watermarking scheme. Thus, for watermark embedding and extraction, same key is required. Therefore the key must be shared between the owner and the verifier via some safe network. This paper demonstrates the performance by considering different qualitative metrics namely Peak Signal to Noise ratio, Structure similarity index and correlation values and also apply some attacks to prove the robustness. The Experimental results are presented to demonstrate that the proposed scheme can withstand a variety of video processing attacks as well as imperceptibility.

Keywords: discrete wavelet transform, robustness, video watermarking, watermark

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345 Selection and Preparation of High Performance, Natural and Cost-Effective Hydrogel as a Bio-Ink for 3D Bio-Printing and Organ on Chip Applications

Authors: Rawan Ashraf, Ahmed E. Gomaa, Gehan Safwat, Ayman Diab

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Background: Three-dimensional (3D) bio-printing has become a versatile and powerful method for generating a variety of biological constructs, including bone or extracellular matrix scaffolds endo- or epithelial, muscle tissue, as well as organoids. Aim of the study: Fabricate a low cost DIY 3D bio-printer to produce 3D bio-printed products such as anti-microbial packaging or multi-organs on chips. We demonstrate the alignment between two types of 3D printer technology (3D Bio-printer and DLP) on Multi-organ-on-a-chip (multi-OoC) devices fabrication. Methods: First, Design and Fabrication of the Syringe Unit for Modification of an Off-the-Shelf 3D Printer, then Preparation of Hydrogel based on natural polymers Sodium Alginate and Gelatin, followed by acquisition of the cell suspension, then modeling the desired 3D structure. Preparation for 3D printing, then Cell-free and cell-laden hydrogels went through the printing process at room temperature under sterile conditions and finally post printing curing process and studying the printed structure regards physical and chemical characteristics. The hard scaffold of the Organ on chip devices was designed and fabricated using the DLP-3D printer, following similar approaches as the Microfluidics system fabrication. Results: The fabricated Bio-Ink was based onHydrogel polymer mix of sodium alginate and gelatin 15% to 0.5%, respectively. Later the 3D printing process was conducted using a higher percentage of alginate-based hydrogels because of it viscosity and the controllable crosslinking, unlike the thermal crosslinking of Gelatin. The hydrogels were colored to simulate the representation of two types of cells. The adaption of the hard scaffold, whether for the Microfluidics system or the hard-tissues, has been acquired by the DLP 3D printers with fabricated natural bioactive essential oils that contain antimicrobial activity, followed by printing in Situ three complex layers of soft-hydrogel as a cell-free Bio-Ink to simulate the real-life tissue engineering process. The final product was a proof of concept for a rapid 3D cell culturing approaches that uses an engineered hard scaffold along with soft-tissues, thus, several applications were offered as products of the current prototype, including the Organ-On-Chip as a successful integration between DLP and 3D bioprinter. Conclusion: Multiple designs for the organ-on-a-chip (multi-OoC) devices have been acquired in our study with main focus on the low cost fabrication of such technology and the potential to revolutionize human health research and development. We describe circumstances in which multi-organ models are useful after briefly examining the requirement for full multi-organ models with a systemic component. Following that, we took a look at the current multi-OoC platforms, such as integrated body-on-a-chip devices and modular techniques that use linked organ-specific modules.

Keywords: 3d bio-printer, hydrogel, multi-organ on chip, bio-inks

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344 LaeA/1-Velvet Interplay in Aspergillus and Trichoderma: Regulation of Secondary Metabolites and Cellulases

Authors: Razieh Karimi Aghcheh, Christian Kubicek, Joseph Strauss, Gerhard Braus

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Filamentous fungi are of considerable economic and social significance for human health, nutrition and in white biotechnology. These organisms are dominant producers of a range of primary metabolites such as citric acid, microbial lipids (biodiesel) and higher unsaturated fatty acids (HUFAs). In particular, they produce also important but structurally complex secondary metabolites with enormous therapeutic applications in pharmaceutical industry, for example: cephalosporin, penicillin, taxol, zeranol and ergot alkaloids. Several fungal secondary metabolites, which are significantly relevant to human health do not only include antibiotics, but also e.g. lovastatin, a well-known antihypercholesterolemic agent produced by Aspergillus. terreus, or aflatoxin, a carcinogen produced by A. flavus. In addition to their roles for human health and agriculture, some fungi are industrially and commercially important: Species of the ascomycete genus Hypocrea spp. (teleomorph of Trichoderma) have been demonstrated as efficient producer of highly active cellulolytic enzymes. This trait makes them effective in disrupting and depolymerization of lignocellulosic materials and thus applicable tools in number of biotechnological areas as diverse as clothes-washing detergent, animal feed, and pulp and fuel productions. Fungal LaeA/LAE1 (Loss of aflR Expression A) homologs their gene products act at the interphase between secondary metabolisms, cellulase production and development. Lack of the corresponding genes results in significant physiological changes including loss of secondary metabolite and lignocellulose degrading enzymes production. At the molecular level, the encoded proteins are presumably methyltransferases or demethylases which act directly or indirectly at heterochromatin and interact with velvet domain proteins. Velvet proteins bind to DNA and affect expression of secondary metabolites (SMs) genes and cellulases. The dynamic interplay between LaeA/LAE1, velvet proteins and additional interaction partners is the key for an understanding of the coordination of metabolic and morphological functions of fungi and is required for a biotechnological control of the formation of desired bioactive products. Aspergilli and Trichoderma represent different biotechnologically significant species with significant differences in the LaeA/LAE1-Velvet protein machinery and their target proteins. We, therefore, performed a comparative study of the interaction partners of this machinery and the dynamics of the various protein-protein interactions using our robust proteomic and mass spectrometry techniques. This enhances our knowledge about the fungal coordination of secondary metabolism, cellulase production and development and thereby will certainly improve recombinant fungal strain construction for the production of industrial secondary metabolite or lignocellulose hydrolytic enzymes.

Keywords: cellulases, LaeA/1, proteomics, secondary metabolites

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343 Attitudes of Gratitude: An Analysis of 30 Cancer Patient Narratives Published by Leading U.S. Cancer Care Centers

Authors: Maria L. McLeod

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This study examines the ways in which cancer patient narratives are portrayed and framed on the websites of three leading U.S. cancer care centers –The University of Texas MD Anderson Cancer Center in Houston, Memorial Sloan Kettering Cancer Center in New York, and Seattle Cancer Care Alliance. Thirty patient stories, ten from each cancer center website blog, were analyzed using qualitative and quantitative textual analysis of unstructured data, documenting repeated use of specific metaphors and tropes while charting common themes and other elements of story structure and content. Patient narratives were coded using grounded theory as the basis for conducting emergent qualitative research. As part of a systematic, inductive approach to collecting and analyzing data, recurrent and unique themes were examined and compared in terms of positive and negative framing, patient agency, and institutional praise. All three of these cancer care centers are teaching hospitals with university affiliations, that emphasizes an evidence-based scientific approach to treatment that utilizes the latest research and cutting-edge techniques and technology. Thus, the use of anecdotal evidence presented in patient narratives could be perceived as being in conflict with this evidence-based model, as the patient stories are not an accurate representation of scientific outcomes related to developing cancer, cancer reoccurrence, or cancer outcomes. The representative patient narratives tend to exclude or downplay adverse responses to treatment, survival rates, integrative and/or complementary cancer treatments, cancer prevention and causes, and barriers to treatment, such as the limitation of insurance plans, costs of treatment, and/or other issues related to access, potentially contributing to false narratives and inaccurate notions of cancer prevention, cancer care treatment and the potential for a cure. Both quantitative and qualitative findings demonstrate that cancer patient stories featured on the blogsites of the nation’s top cancer care centers deemphasize patient agency and, instead, emphasize deference and gratitude toward the institutions where the featured patients received treatment. Along these lines, language choices reflect positive framing of the cancer experience. Accompanying portrait photos of healthy appearing subjects as well as positive-framed headlines, subheads, and pull quotes function similarly, reflecting hopeful, transformative experiences and outcomes over hardship and suffering. Although patient narratives include real, factual scientific details and descriptions of actual events, the stories lack references to more negative realities of cancer diagnosis and treatment. Instead, they emphasize the triumph of survival by which the cancer care center, in the savior/hero role, enables the patient’s success, represented as a cathartic medical journey.

Keywords: cancer framing, cancer stories, medical gaze, patient narratives

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342 Case-Based Reasoning for Modelling Random Variables in the Reliability Assessment of Existing Structures

Authors: Francesca Marsili

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The reliability assessment of existing structures with probabilistic methods is becoming an increasingly important and frequent engineering task. However probabilistic reliability methods are based on an exhaustive knowledge of the stochastic modeling of the variables involved in the assessment; at the moment standards for the modeling of variables are absent, representing an obstacle to the dissemination of probabilistic methods. The framework according to probability distribution functions (PDFs) are established is represented by the Bayesian statistics, which uses Bayes Theorem: a prior PDF for the considered parameter is established based on information derived from the design stage and qualitative judgments based on the engineer past experience; then, the prior model is updated with the results of investigation carried out on the considered structure, such as material testing, determination of action and structural properties. The application of Bayesian statistics arises two different kind of problems: 1. The results of the updating depend on the engineer previous experience; 2. The updating of the prior PDF can be performed only if the structure has been tested, and quantitative data that can be statistically manipulated have been collected; performing tests is always an expensive and time consuming operation; furthermore, if the considered structure is an ancient building, destructive tests could compromise its cultural value and therefore should be avoided. In order to solve those problems, an interesting research path is represented by investigating Artificial Intelligence (AI) techniques that can be useful for the automation of the modeling of variables and for the updating of material parameters without performing destructive tests. Among the others, one that raises particular attention in relation to the object of this study is constituted by Case-Based Reasoning (CBR). In this application, cases will be represented by existing buildings where material tests have already been carried out and an updated PDFs for the material mechanical parameters has been computed through a Bayesian analysis. Then each case will be composed by a qualitative description of the material under assessment and the posterior PDFs that describe its material properties. The problem that will be solved is the definition of PDFs for material parameters involved in the reliability assessment of the considered structure. A CBR system represent a good candi¬date in automating the modelling of variables because: 1. Engineers already draw an estimation of the material properties based on the experience collected during the assessment of similar structures, or based on similar cases collected in literature or in data-bases; 2. Material tests carried out on structure can be easily collected from laboratory database or from literature; 3. The system will provide the user of a reliable probabilistic description of the variables involved in the assessment that will also serve as a tool in support of the engineer’s qualitative judgments. Automated modeling of variables can help in spreading probabilistic reliability assessment of existing buildings in the common engineering practice, and target at the best intervention and further tests on the structure; CBR represents a technique which may help to achieve this.

Keywords: reliability assessment of existing buildings, Bayesian analysis, case-based reasoning, historical structures

Procedia PDF Downloads 339
341 Computational Team Dynamics and Interaction Patterns in New Product Development Teams

Authors: Shankaran Sitarama

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New Product Development (NPD) is invariably a team effort and involves effective teamwork. NPD team has members from different disciplines coming together and working through the different phases all the way from conceptual design phase till the production and product roll out. Creativity and Innovation are some of the key factors of successful NPD. Team members going through the different phases of NPD interact and work closely yet challenge each other during the design phases to brainstorm on ideas and later converge to work together. These two traits require the teams to have a divergent and a convergent thinking simultaneously. There needs to be a good balance. The team dynamics invariably result in conflicts among team members. While some amount of conflict (ideational conflict) is desirable in NPD teams to be creative as a group, relational conflicts (or discords among members) could be detrimental to teamwork. Team communication truly reflect these tensions and team dynamics. In this research, team communication (emails) between the members of the NPD teams is considered for analysis. The email communication is processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. The amount of communication (content and not frequency of communication) defines the interaction strength between the members. Social network adjacency matrix is thus obtained for the team. Standard social network analysis techniques based on the Adjacency Matrix (AM) and Dichotomized Adjacency Matrix (DAM) based on network density yield network graphs and network metrics like centrality. The social network graphs are then rendered for visual representation using a Metric Multi-Dimensional Scaling (MMDS) algorithm for node placements and arcs connecting the nodes (representing team members) are drawn. The distance of the nodes in the placement represents the tie-strength between the members. Stronger tie-strengths render nodes closer. Overall visual representation of the social network graph provides a clear picture of the team’s interactions. This research reveals four distinct patterns of team interaction that are clearly identifiable in the visual representation of the social network graph and have a clearly defined computational scheme. The four computational patterns of team interaction defined are Central Member Pattern (CMP), Subgroup and Aloof member Pattern (SAP), Isolate Member Pattern (IMP), and Pendant Member Pattern (PMP). Each of these patterns has a team dynamics implication in terms of the conflict level in the team. For instance, Isolate member pattern, clearly points to a near break-down in communication with the member and hence a possible high conflict level, whereas the subgroup or aloof member pattern points to a non-uniform information flow in the team and some moderate level of conflict. These pattern classifications of teams are then compared and correlated to the real level of conflict in the teams as indicated by the team members through an elaborate self-evaluation, team reflection, feedback form and results show a good correlation.

Keywords: team dynamics, team communication, team interactions, social network analysis, sna, new product development, latent semantic analysis, LSA, NPD teams

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340 Unveiling the Dynamics of Preservice Teachers’ Engagement with Mathematical Modeling through Model Eliciting Activities: A Comprehensive Exploration of Acceptance and Resistance Towards Modeling and Its Pedagogy

Authors: Ozgul Kartal, Wade Tillett, Lyn D. English

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Despite its global significance in curricula, mathematical modeling encounters persistent disparities in recognition and emphasis within regular mathematics classrooms and teacher education across countries with diverse educational and cultural traditions, including variations in the perceived role of mathematical modeling. Over the past two decades, increased attention has been given to the integration of mathematical modeling into national curriculum standards in the U.S. and other countries. Therefore, the mathematics education research community has dedicated significant efforts to investigate various aspects associated with the teaching and learning of mathematical modeling, primarily focusing on exploring the applicability of modeling in schools and assessing students', teachers', and preservice teachers' (PTs) competencies and engagement in modeling cycles and processes. However, limited attention has been directed toward examining potential resistance hindering teachers and PTs from effectively implementing mathematical modeling. This study focuses on how PTs, without prior modeling experience, resist and/or embrace mathematical modeling and its pedagogy as they learn about models and modeling perspectives, navigate the modeling process, design and implement their modeling activities and lesson plans, and experience the pedagogy enabling modeling. Model eliciting activities (MEAs) were employed due to their high potential to support the development of mathematical modeling pedagogy. The mathematical modeling module was integrated into a mathematics methods course to explore how PTs embraced or resisted mathematical modeling and its pedagogy. The module design included reading, reflecting, engaging in modeling, assessing models, creating a modeling task (MEA), and designing a modeling lesson employing an MEA. Twelve senior undergraduate students participated, and data collection involved video recordings, written prompts, lesson plans, and reflections. An open coding analysis revealed acceptance and resistance toward teaching mathematical modeling. The study identified four overarching themes, including both acceptance and resistance: pedagogy, affordance of modeling (tasks), modeling actions, and adjusting modeling. In the category of pedagogy, PTs displayed acceptance based on potential pedagogical benefits and resistance due to various concerns. The affordance of modeling (tasks) category emerged from instances when PTs showed acceptance or resistance while discussing the nature and quality of modeling tasks, often debating whether modeling is considered mathematics. PTs demonstrated both acceptance and resistance in their modeling actions, engaging in modeling cycles as students and designing/implementing MEAs as teachers. The adjusting modeling category captured instances where PTs accepted or resisted maintaining the qualities and nature of the modeling experience or converted modeling into a typical structured mathematics experience for students. While PTs displayed a mix of acceptance and resistance in their modeling actions, limitations were observed in embracing complexity and adhering to model principles. The study provides valuable insights into the challenges and opportunities of integrating mathematical modeling into teacher education, emphasizing the importance of addressing pedagogical concerns and providing support for effective implementation. In conclusion, this research offers a comprehensive understanding of PTs' engagement with modeling, advocating for a more focused discussion on the distinct nature and significance of mathematical modeling in the broader curriculum to establish a foundation for effective teacher education programs.

Keywords: mathematical modeling, model eliciting activities, modeling pedagogy, secondary teacher education

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339 Accelerating Personalization Using Digital Tools to Drive Circular Fashion

Authors: Shamini Dhana, G. Subrahmanya VRK Rao

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The fashion industry is advancing towards a mindset of zero waste, personalization, creativity, and circularity. The trend of upcycling clothing and materials into personalized fashion is being demanded by the next generation. There is a need for a digital tool to accelerate the process towards mass customization. Dhana’s D/Sphere fashion technology platform uses digital tools to accelerate upcycling. In essence, advanced fashion garments can be designed and developed via reuse, repurposing, recreating activities, and using existing fabric and circulating materials. The D/Sphere platform has the following objectives: to provide (1) An opportunity to develop modern fashion using existing, finished materials and clothing without chemicals or water consumption; (2) The potential for an everyday customer and designer to use the medium of fashion for creative expression; (3) A solution to address the global textile waste generated by pre- and post-consumer fashion; (4) A solution to reduce carbon emissions, water, and energy consumption with the participation of all stakeholders; (5) An opportunity for brands, manufacturers, retailers to work towards zero-waste designs and as an alternative revenue stream. Other benefits of this alternative approach include sustainability metrics, trend prediction, facilitation of disassembly and remanufacture deep learning, and hyperheuristics for high accuracy. A design tool for mass personalization and customization utilizing existing circulating materials and deadstock, targeted to fashion stakeholders will lower environmental costs, increase revenues through up to date upcycled apparel, produce less textile waste during the cut-sew-stitch process, and provide a real design solution for the end customer to be part of circular fashion. The broader impact of this technology will result in a different mindset to circular fashion, increase the value of the product through multiple life cycles, find alternatives towards zero waste, and reduce the textile waste that ends up in landfills. This technology platform will be of interest to brands and companies that have the responsibility to reduce their environmental impact and contribution to climate change as it pertains to the fashion and apparel industry. Today, over 70% of the $3 trillion fashion and apparel industry ends up in landfills. To this extent, the industry needs such alternative techniques to both address global textile waste as well as provide an opportunity to include all stakeholders and drive circular fashion with new personalized products. This type of modern systems thinking is currently being explored around the world by the private sector, organizations, research institutions, and governments. This technological innovation using digital tools has the potential to revolutionize the way we look at communication, capabilities, and collaborative opportunities amongst stakeholders in the development of new personalized and customized products, as well as its positive impacts on society, our environment, and global climate change.

Keywords: circular fashion, deep learning, digital technology platform, personalization

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338 Development of Advanced Virtual Radiation Detection and Measurement Laboratory (AVR-DML) for Nuclear Science and Engineering Students

Authors: Lily Ranjbar, Haori Yang

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Online education has been around for several decades, but the importance of online education became evident after the COVID-19 pandemic. Eventhough the online delivery approach works well for knowledge building through delivering content and oversight processes, it has limitations in developing hands-on laboratory skills, especially in the STEM field. During the pandemic, many education institutions faced numerous challenges in delivering lab-based courses, especially in the STEM field. Also, many students worldwide were unable to practice working with lab equipment due to social distancing or the significant cost of highly specialized equipment. The laboratory plays a crucial role in nuclear science and engineering education. It can engage students and improve their learning outcomes. In addition, online education and virtual labs have gained substantial popularity in engineering and science education. Therefore, developing virtual labs is vital for institutions to deliver high-class education to their students, including their online students. The School of Nuclear Science and Engineering (NSE) at Oregon State University, in partnership with SpectralLabs company, has developed an Advanced Virtual Radiation Detection and Measurement Lab (AVR-DML) to offer a fully online Master of Health Physics program. It was essential for us to use a system that could simulate nuclear modules that accurately replicate the underlying physics, the nature of radiation and radiation transport, and the mechanics of the instrumentations used in the real radiation detection lab. It was all accomplished using a Realistic, Adaptive, Interactive Learning System (RAILS). RAILS is a comprehensive software simulation-based learning system for use in training. It is comprised of a web-based learning management system that is located on a central server, as well as a 3D-simulation package that is downloaded locally to user machines. Users will find that the graphics, animations, and sounds in RAILS create a realistic, immersive environment to practice detecting different radiation sources. These features allow students to coexist, interact and engage with a real STEM lab in all its dimensions. It enables them to feel like they are in a real lab environment and to see the same system they would in a lab. Unique interactive interfaces were designed and developed by integrating all the tools and equipment needed to run each lab. These interfaces provide students full functionality for data collection, changing the experimental setup, and live data collection with real-time updates for each experiment. Students can manually do all experimental setups and parameter changes in this lab. Experimental results can then be tracked and analyzed in an oscilloscope, a multi-channel analyzer, or a single-channel analyzer (SCA). The advanced virtual radiation detection and measurement laboratory developed in this study enabled the NSE school to offer a fully online MHP program. This flexibility of course modality helped us to attract more non-traditional students, including international students. It is a valuable educational tool as students can walk around the virtual lab, make mistakes, and learn from them. They have an unlimited amount of time to repeat and engage in experiments. This lab will also help us speed up training in nuclear science and engineering.

Keywords: advanced radiation detection and measurement, virtual laboratory, realistic adaptive interactive learning system (rails), online education in stem fields, student engagement, stem online education, stem laboratory, online engineering education

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337 Monitoring and Improving Performance of Soil Aquifer Treatment System and Infiltration Basins Performance: North Gaza Emergency Sewage Treatment Plant as Case Study

Authors: Sadi Ali, Yaser Kishawi

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As part of Palestine, Gaza Strip (365 km2 and 1.8 million habitants) is considered a semi-arid zone relies solely on the Coastal Aquifer. The coastal aquifer is only source of water with only 5-10% suitable for human use. This barely cover the domestic and agricultural needs of Gaza Strip. Palestinian Water Authority Strategy is to find non-conventional water resource from treated wastewater to irrigate 1500 hectares and serves over 100,000 inhabitants. A new WWTP project is to replace the old-overloaded Biet Lahia WWTP. The project consists of three parts; phase A (pressure line & 9 infiltration basins - IBs), phase B (a new WWTP) and phase C (Recovery and Reuse Scheme – RRS – to capture the spreading plume). Currently, phase A is functioning since Apr 2009. Since Apr 2009, a monitoring plan is conducted to monitor the infiltration rate (I.R.) of the 9 basins. Nearly 23 million m3 of partially treated wastewater were infiltrated up to Jun 2014. It is important to maintain an acceptable rate to allow the basins to handle the coming quantities (currently 10,000 m3 are pumped an infiltrated daily). The methodology applied was to review and analysis the collected data including the I.R.s, the WW quality and the drying-wetting schedule of the basins. One of the main findings is the relation between the Total Suspended Solids (TSS) at BLWWTP and the I.R. at the basins. Since April 2009, the basins scored an average I.R. of about 2.5 m/day. Since then the records showed a decreasing pattern of the average rate until it reached the lower value of 0.42 m/day in Jun 2013. This was accompanied with an increase of TSS (mg/L) concentration at the source reaching above 200 mg/L. The reducing of TSS concentration directly improved the I.R. (by cleaning the WW source ponds at Biet Lahia WWTP site). This was reflected in an improvement in I.R. in last 6 months from 0.42 m/day to 0.66 m/day then to nearly 1.0 m/day as the average of the last 3 months of 2013. The wetting-drying scheme of the basins was observed (3 days wetting and 7 days drying) besides the rainfall rates. Despite the difficulty to apply this scheme accurately a control of flow to each basin was applied to improve the I.R. The drying-wetting system affected the I.R. of individual basins, thus affected the overall system rate which was recorded and assessed. Also the ploughing activities at the infiltration basins as well were recommended at certain times to retain a certain infiltration level. This breaks the confined clogging layer which prevents the infiltration. It is recommended to maintain proper quality of WW infiltrated to ensure an acceptable performance of IBs. The continual maintenance of settling ponds at BLWWTP, continual ploughing of basins and applying soil treatment techniques at the IBs will improve the I.R.s. When the new WWTP functions a high standard effluent quality (TSS 20mg, BOD 20 mg/l and TN 15 mg/l) will be infiltrated, thus will enhance I.R.s of IBs due to lower organic load.

Keywords: SAT, wastewater quality, soil remediation, North Gaza

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336 Reliability and Availability Analysis of Satellite Data Reception System using Reliability Modeling

Authors: Ch. Sridevi, S. P. Shailender Kumar, B. Gurudayal, A. Chalapathi Rao, K. Koteswara Rao, P. Srinivasulu

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System reliability and system availability evaluation plays a crucial role in ensuring the seamless operation of complex satellite data reception system with consistent performance for longer periods. This paper presents a novel approach for the same using a case study on one of the antenna systems at satellite data reception ground station in India. The methodology involves analyzing system's components, their failure rates, system's architecture, generation of logical reliability block diagram model and estimating the reliability of the system using the component level mean time between failures considering exponential distribution to derive a baseline estimate of the system's reliability. The model is then validated with collected system level field failure data from the operational satellite data reception systems that includes failure occurred, failure time, criticality of the failure and repair times by using statistical techniques like median rank, regression and Weibull analysis to extract meaningful insights regarding failure patterns and practical reliability of the system and to assess the accuracy of the developed reliability model. The study mainly focused on identification of critical units within the system, which are prone to failures and have a significant impact on overall performance and brought out a reliability model of the identified critical unit. This model takes into account the interdependencies among system components and their impact on overall system reliability and provides valuable insights into the performance of the system to understand the Improvement or degradation of the system over a period of time and will be the vital input to arrive at the optimized design for future development. It also provides a plug and play framework to understand the effect on performance of the system in case of any up gradations or new designs of the unit. It helps in effective planning and formulating contingency plans to address potential system failures, ensuring the continuity of operations. Furthermore, to instill confidence in system users, the duration for which the system can operate continuously with the desired level of 3 sigma reliability was estimated that turned out to be a vital input to maintenance plan. System availability and station availability was also assessed by considering scenarios of clash and non-clash to determine the overall system performance and potential bottlenecks. Overall, this paper establishes a comprehensive methodology for reliability and availability analysis of complex satellite data reception systems. The results derived from this approach facilitate effective planning contingency measures, and provide users with confidence in system performance and enables decision-makers to make informed choices about system maintenance, upgrades and replacements. It also aids in identifying critical units and assessing system availability in various scenarios and helps in minimizing downtime and optimizing resource allocation.

Keywords: exponential distribution, reliability modeling, reliability block diagram, satellite data reception system, system availability, weibull analysis

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335 The Practical Application of Sensory Awareness in Developing Healthy Communication, Emotional Regulation, and Emotional Introspection

Authors: Node Smith

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Developmental psychology has long focused on modeling consciousness, often neglecting practical application and clinical utility. This paper aims to bridge this gap by exploring the practical application of physical and sensory tracking and awareness in fostering essential skills for conscious development. Higher conscious development requires practical skills such as self-agency, the ability to hold multiple perspectives, and genuine altruism. These are not personality characteristics but areas of skillfulness that address many cultural deficiencies impacting our world. They are intertwined with individual as well as collective conscious development. Physical, sensory tracking and awareness are crucial for developing these skills and offer the added benefit of cultivating healthy communication, emotional regulation, and introspection. Unlike skills such as throwing a baseball, which can be developed through practice or innate ability, the ability to introspect, track physical sensations, and observe oneself objectively is essential for advancing consciousness. Lacking these skills leads to cultural and individual anxiety, helplessness, and a lack of agency, manifesting as blame-shifting and irresponsibility. The inability to hold multiple perspectives stifles altruism, as genuine consideration for a global community requires accepting other perspectives without conditions. Physical and sensory tracking enhances self-awareness by grounding individuals in their bodily experiences. This grounding is critical for emotional regulation, allowing individuals to identify and process emotions in real-time, preventing overwhelm and fostering balance. Techniques like mindfulness meditation and body scan exercises attune individuals to their physical sensations, providing insights into their emotional states. Sensory awareness also facilitates healthy communication by fostering empathy and active listening. When individuals are in tune with their physical sensations, they become more present in interactions, picking up on subtle cues and responding thoughtfully. This presence reduces misunderstandings and conflicts, promoting more effective communication. The ability to introspect and observe oneself objectively is key to emotional introspection. This skill allows individuals to reflect on their thoughts, feelings, and behaviors, identify patterns, recognize areas for growth, and make conscious choices aligned with their values and goals. In conclusion, physical and sensory tracking and awareness are vital for developing the skills necessary for higher consciousness development. By fostering self-agency, emotional regulation, and the ability to hold multiple perspectives, these practices contribute to healthier communication, deeper emotional introspection, and a more altruistic and connected global community. Integrating these practices into developmental psychology and therapeutic interventions holds significant promise for both individual and societal transformation.

Keywords: conscious development, emotional introspection, emotional regulation, self-agency, stages of development

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334 Green Architecture from the Thawing Arctic: Reconstructing Traditions for Future Resilience

Authors: Nancy Mackin

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Historically, architects from Aalto to Gaudi to Wright have looked to the architectural knowledge of long-resident peoples for forms and structural principles specifically adapted to the regional climate, geology, materials availability, and culture. In this research, structures traditionally built by Inuit peoples in a remote region of the Canadian high Arctic provides a folio of architectural ideas that are increasingly relevant during these times of escalating carbon emissions and climate change. ‘Green architecture from the Thawing Arctic’ researches, draws, models, and reconstructs traditional buildings of Inuit (Eskimo) peoples in three remote, often inaccessible Arctic communities. Structures verified in pre-contact oral history and early written history are first recorded in architectural drawings, then modeled and, with the participation of Inuit young people, local scientists, and Elders, reconstructed as emergency shelters. Three full-sized building types are constructed: a driftwood and turf-clad A-frame (spring/summer); a stone/bone/turf house with inwardly spiraling walls and a fan-shaped floor plan (autumn); and a parabolic/catenary arch-shaped dome from willow, turf, and skins (autumn/winter). Each reconstruction is filmed and featured in a short video. Communities found that the reconstructed buildings and the method of involving young people and Elders in the reconstructions have on-going usefulness, as follows: 1) The reconstructions provide emergency shelters, particularly needed as climate change worsens storms, floods, and freeze-thaw cycles and scientists and food harvesters who must work out of the land become stranded more frequently; 2) People from the communities re-learned from their Elders how to use materials from close at hand to construct impromptu shelters; 3) Forms from tradition, such as windbreaks at entrances and using levels to trap warmth within winter buildings, can be adapted and used in modern community buildings and housing; and 4) The project initiates much-needed educational and employment opportunities in the applied sciences (engineering and architecture), construction, and climate change monitoring, all offered in a culturally-responsive way. Elders, architects, scientists, and young people added innovations to the traditions as they worked, thereby suggesting new sustainable, culturally-meaningful building forms and materials combinations that can be used for modern buildings. Adding to the growing interest in bio-mimicry, participants looked at properties of Arctic and subarctic materials such as moss (insulation), shrub bark (waterproofing), and willow withes (parabolic and catenary arched forms). ‘Green Architecture from the Thawing Arctic’ demonstrates the effective, useful architectural oeuvre of a resilient northern people. The research parallels efforts elsewhere in the world to revitalize long-resident peoples’ architectural knowledge, in the interests of designing sustainable buildings that reflect culture, heritage, and identity.

Keywords: architectural culture and identity, climate change, forms from nature, Inuit architecture, locally sourced biodegradable materials, traditional architectural knowledge, traditional Inuit knowledge

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333 Seafloor and Sea Surface Modelling in the East Coast Region of North America

Authors: Magdalena Idzikowska, Katarzyna Pająk, Kamil Kowalczyk

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Seafloor topography is a fundamental issue in geological, geophysical, and oceanographic studies. Single-beam or multibeam sonars attached to the hulls of ships are used to emit a hydroacoustic signal from transducers and reproduce the topography of the seabed. This solution provides relevant accuracy and spatial resolution. Bathymetric data from ships surveys provides National Centers for Environmental Information – National Oceanic and Atmospheric Administration. Unfortunately, most of the seabed is still unidentified, as there are still many gaps to be explored between ship survey tracks. Moreover, such measurements are very expensive and time-consuming. The solution is raster bathymetric models shared by The General Bathymetric Chart of the Oceans. The offered products are a compilation of different sets of data - raw or processed. Indirect data for the development of bathymetric models are also measurements of gravity anomalies. Some forms of seafloor relief (e.g. seamounts) increase the force of the Earth's pull, leading to changes in the sea surface. Based on satellite altimetry data, Sea Surface Height and marine gravity anomalies can be estimated, and based on the anomalies, it’s possible to infer the structure of the seabed. The main goal of the work is to create regional bathymetric models and models of the sea surface in the area of the east coast of North America – a region of seamounts and undulating seafloor. The research includes an analysis of the methods and techniques used, an evaluation of the interpolation algorithms used, model thickening, and the creation of grid models. Obtained data are raster bathymetric models in NetCDF format, survey data from multibeam soundings in MB-System format, and satellite altimetry data from Copernicus Marine Environment Monitoring Service. The methodology includes data extraction, processing, mapping, and spatial analysis. Visualization of the obtained results was carried out with Geographic Information System tools. The result is an extension of the state of the knowledge of the quality and usefulness of the data used for seabed and sea surface modeling and knowledge of the accuracy of the generated models. Sea level is averaged over time and space (excluding waves, tides, etc.). Its changes, along with knowledge of the topography of the ocean floor - inform us indirectly about the volume of the entire water ocean. The true shape of the ocean surface is further varied by such phenomena as tides, differences in atmospheric pressure, wind systems, thermal expansion of water, or phases of ocean circulation. Depending on the location of the point, the higher the depth, the lower the trend of sea level change. Studies show that combining data sets, from different sources, with different accuracies can affect the quality of sea surface and seafloor topography models.

Keywords: seafloor, sea surface height, bathymetry, satellite altimetry

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332 Challenges to Developing a Trans-European Programme for Health Professionals to Recognize and Respond to Survivors of Domestic Violence and Abuse

Authors: June Keeling, Christina Athanasiades, Vaiva Hendrixson, Delyth Wyndham

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Recognition and education in violence, abuse, and neglect for medical and healthcare practitioners (REVAMP) is a trans-European project aiming to introduce a training programme that has been specifically developed by partners across seven European countries to meet the needs of medical and healthcare practitioners. Amalgamating the knowledge and experience of clinicians, researchers, and educators from interdisciplinary and multi-professional backgrounds, REVAMP has tackled the under-resourced and underdeveloped area of domestic violence and abuse. The team designed an online training programme to support medical and healthcare practitioners to recognise and respond appropriately to survivors of domestic violence and abuse at their point of contact with a health provider. The REVAMP partner countries include Europe: France, Lithuania, Germany, Greece, Iceland, Norway, and the UK. The training is delivered through a series of interactive online modules, adapting evidence-based pedagogical approaches to learning. Capturing and addressing the complexities of the project impacted the methodological decisions and approaches to evaluation. The challenge was to find an evaluation methodology that captured valid data across all partner languages to demonstrate the extent of the change in knowledge and understanding. Co-development by all team members was a lengthy iterative process, challenged by a lack of consistency in terminology. A mixed methods approach enabled both qualitative and quantitative data to be collected, at the start, during, and at the conclusion of the training for the purposes of evaluation. The module content and evaluation instrument were accessible in each partner country's language. Collecting both types of data provided a high-level snapshot of attainment via the quantitative dataset and an in-depth understanding of the impact of the training from the qualitative dataset. The analysis was mixed methods, with integration at multiple interfaces. The primary focus of the analysis was to support the overall project evaluation for the funding agency. A key project outcome was identifying that the trans-European approach posed several challenges. Firstly, the project partners did not share a first language or a legal or professional approach to domestic abuse and neglect. This was negotiated through complex, systematic, and iterative interaction between team members so that consensus could be achieved. Secondly, the context of the data collection in several different cultural, educational, and healthcare systems across Europe challenged the development of a robust evaluation. The participants in the pilot evaluation shared that the training was contemporary, well-designed, and of great relevance to inform practice. Initial results from the evaluation indicated that the participants were drawn from more than eight partner countries due to the online nature of the training. The primary results indicated a high level of engagement with the content and achievement through the online assessment. The main finding was that the participants perceived the impact of domestic abuse and neglect in very different ways in their individual professional contexts. Most significantly, the participants recognised the need for the training and the gap that existed previously. It is notable that a mixed-methods evaluation of a trans-European project is unusual at this scale.

Keywords: domestic violence, e-learning, health professionals, trans-European

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331 ChatGPT 4.0 Demonstrates Strong Performance in Standardised Medical Licensing Examinations: Insights and Implications for Medical Educators

Authors: K. O'Malley

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Background: The emergence and rapid evolution of large language models (LLMs) (i.e., models of generative artificial intelligence, or AI) has been unprecedented. ChatGPT is one of the most widely used LLM platforms. Using natural language processing technology, it generates customized responses to user prompts, enabling it to mimic human conversation. Responses are generated using predictive modeling of vast internet text and data swathes and are further refined and reinforced through user feedback. The popularity of LLMs is increasing, with a growing number of students utilizing these platforms for study and revision purposes. Notwithstanding its many novel applications, LLM technology is inherently susceptible to bias and error. This poses a significant challenge in the educational setting, where academic integrity may be undermined. This study aims to evaluate the performance of the latest iteration of ChatGPT (ChatGPT4.0) in standardized state medical licensing examinations. Methods: A considered search strategy was used to interrogate the PubMed electronic database. The keywords ‘ChatGPT’ AND ‘medical education’ OR ‘medical school’ OR ‘medical licensing exam’ were used to identify relevant literature. The search included all peer-reviewed literature published in the past five years. The search was limited to publications in the English language only. Eligibility was ascertained based on the study title and abstract and confirmed by consulting the full-text document. Data was extracted into a Microsoft Excel document for analysis. Results: The search yielded 345 publications that were screened. 225 original articles were identified, of which 11 met the pre-determined criteria for inclusion in a narrative synthesis. These studies included performance assessments in national medical licensing examinations from the United States, United Kingdom, Saudi Arabia, Poland, Taiwan, Japan and Germany. ChatGPT 4.0 achieved scores ranging from 67.1 to 88.6 percent. The mean score across all studies was 82.49 percent (SD= 5.95). In all studies, ChatGPT exceeded the threshold for a passing grade in the corresponding exam. Conclusion: The capabilities of ChatGPT in standardized academic assessment in medicine are robust. While this technology can potentially revolutionize higher education, it also presents several challenges with which educators have not had to contend before. The overall strong performance of ChatGPT, as outlined above, may lend itself to unfair use (such as the plagiarism of deliverable coursework) and pose unforeseen ethical challenges (arising from algorithmic bias). Conversely, it highlights potential pitfalls if users assume LLM-generated content to be entirely accurate. In the aforementioned studies, ChatGPT exhibits a margin of error between 11.4 and 32.9 percent, which resonates strongly with concerns regarding the quality and veracity of LLM-generated content. It is imperative to highlight these limitations, particularly to students in the early stages of their education who are less likely to possess the requisite insight or knowledge to recognize errors, inaccuracies or false information. Educators must inform themselves of these emerging challenges to effectively address them and mitigate potential disruption in academic fora.

Keywords: artificial intelligence, ChatGPT, generative ai, large language models, licensing exam, medical education, medicine, university

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330 Giving Children with Osteogenesis Imperfecta a Voice: Overview of a Participatory Approach for the Development of an Interactive Communication Tool

Authors: M. Siedlikowski, F. Rauch, A. Tsimicalis

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Osteogenesis Imperfecta (OI) is a genetic disorder of childhood onset that causes frequent fractures after minimal physical stress. To date, OI research has focused on medically- and surgically-oriented outcomes with little attention on the perspective of the affected child. It is a challenge to elicit the child’s voice in health care, in other words, their own perspective on their symptoms, but software development offers a way forward. Sisom (Norwegian acronym derived from ‘Si det som det er’ meaning ‘Tell it as it is’) is an award-winning, rigorously tested, interactive, computerized tool that helps children with chronic illnesses express their symptoms to their clinicians. The successful Sisom software tool, that addresses the child directly, has not yet been adapted to attend to symptoms unique to children with OI. The purpose of this study was to develop a Sisom paper prototype for children with OI by seeking the perspectives of end users, particularly, children with OI and clinicians. Our descriptive qualitative study was conducted at Shriners Hospitals for Children® – Canada, which follows the largest cohort of children with OI in North America. Purposive sampling was used to recruit 12 children with OI over three cycles. Nine clinicians oversaw the development process, which involved determining the relevance of current Sisom symptoms, vignettes, and avatars, as well as generating new Sisom OI components. Data, including field notes, transcribed audio-recordings, and drawings, were deductively analyzed using content analysis techniques. Guided by the following framework, data pertaining to symptoms, vignettes, and avatars were coded into five categories: a) Relevant; b) Irrelevant; c) To modify; d) To add; e) Unsure. Overall, 70.8% of Sisom symptoms were deemed relevant for inclusion, with 49.4% directly incorporated, and 21.3% incorporated with changes to syntax, and/or vignette, and/or location. Three additions were made to the ‘Avatar’ island. This allowed children to celebrate their uniqueness: ‘Makes you feel like you’re not like everybody else.’ One new island, ‘About Me’, was added to capture children’s worldviews. One new sub-island, ‘Getting Around’, was added to reflect accessibility issues. These issues were related to the children’s independence, their social lives, as well as the perceptions of others. In being consulted as experts throughout the co-creation of the Sisom OI paper prototype, children coded the Sisom symptoms and provided sound rationales for their chosen codes. In rationalizing their codes, all children shared personal stories about themselves and their relationships, insights about their OI, and an understanding of the strengths and challenges they experience on a day-to-day basis. The child’s perspective on their health is a basic right, and allowing it to be heard is the next frontier in the care of children with genetic diseases. Sisom OI, a methodological breakthrough within OI research, will offer clinicians an innovative and child-centered approach to capture this neglected perspective. It will provide a tool for the delivery of health care in the center that established the worldwide standard of care for children with OI.

Keywords: child health, interactive computerized communication tool, participatory approach, symptom management

Procedia PDF Downloads 157
329 Selfie: Redefining Culture of Narcissism

Authors: Junali Deka

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“Pictures speak more than a thousand words”. It is the power of image which can have multiple meanings the way it is read by the viewers. This research article is an outcome of the extensive study of the phenomenon of‘selfie culture’ and dire need of self-constructed virtual identity among youths. In the recent times, there has been a revolutionary change in the concept of photography in terms of both techniques and applications. The popularity of ‘self-portraits’ mainly depend on the temporal space and time created on social networking sites like Facebook, Instagram. With reference to Stuart’s Hall encoding and decoding process, the article studies the behavior of the users who post photographs online. The photographic messages (Roland Barthes) are interpreted differently by different viewers. The notion of ‘self’, ‘self-love and practice of looking (Marita Sturken) and ways of seeing (John Berger) got new definition and dimensional together. After Oscars Night, show host Ellen DeGeneres’s selfie created the most buzz and hype in the social media. The term was judged the word of 2013, and has earned its place in the dictionary. “In November 2013, the word "selfie" was announced as being the "word of the year" by the Oxford English Dictionary. By the end of 2012, Time magazine considered selfie one of the "top 10 buzzwords" of that year; although selfies had existed long before, it was in 2012 that the term "really hit the big time an Australian origin. The present study was carried to understand the concept of ‘selfie-bug’ and the phenomenon it has created among youth (especially students) at large in developing a pseudo-image of its own. The topic was relevant and gave a platform to discuss about the cultural, psychological and sociological implications of selfie in the age of digital technology. At the first level, content analysis of the primary and secondary sources including newspapers articles and online resources was carried out followed by a small online survey conducted with the help of questionnaire to find out the student’s view on selfie and its social and psychological effects. The newspapers reports and online resources confirmed that selfie is a new trend in the digital media and it has redefined the notion of beauty and self-love. The Facebook and Instagram are the major platforms used to express one-self and creation of virtual identity. The findings clearly reflected the active participation of female students in comparison to male students. The study of the photographs of few selected respondents revealed the difference of attitude and image building among male and female users. The study underlines some basic questions about the desire of reconstruction of identity among young generation, such as - are they becoming culturally narcissist; responsible factors for cultural, social and moral changes in the society, psychological and technological effects caused by Smartphone as well, culminating into a big question mark whether the selfie is a social signifier of identity construction.

Keywords: Culture, Narcissist, Photographs, Selfie

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328 Developing Primal Teachers beyond the Classroom: The Quadrant Intelligence (Q-I) Model

Authors: Alexander K. Edwards

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Introduction: The moral dimension of teacher education globally has assumed a new paradigm of thinking based on the public gain (return-on-investments), value-creation (quality), professionalism (practice), and business strategies (innovations). Abundant literature reveals an interesting revolutionary trend in complimenting the raising of teachers and academic performances. Because of the global competition in the knowledge-creation and service areas, the C21st teacher at all levels is expected to be resourceful, strategic thinker, socially intelligent, relationship aptitude, and entrepreneur astute. This study is a significant contribution to practice and innovations to raise exemplary or primal teachers. In this study, the qualities needed were considered as ‘Quadrant Intelligence (Q-i)’ model for a primal teacher leadership beyond the classroom. The researcher started by examining the issue of the majority of teachers in Ghana Education Services (GES) in need of this Q-i to be effective and efficient. The conceptual framing became determinants of such Q-i. This is significant for global employability and versatility in teacher education to create premium and primal teacher leadership, which are again gaining high attention in scholarship due to failing schools. The moral aspect of teachers failing learners is a highly important discussion. In GES, some schools score zero percent at the basic education certificate examination (BECE). The question is what will make any professional teacher highly productive, marketable, and an entrepreneur? What will give teachers the moral consciousness of doing the best to succeed? Method: This study set out to develop a model for primal teachers in GES as an innovative way to highlight a premium development for the C21st business-education acumen through desk reviews. The study is conceptually framed by examining certain skill sets such as strategic thinking, social intelligence, relational and emotional intelligence and entrepreneurship to answer three main burning questions and other hypotheses. Then the study applied the causal comparative methodology with a purposive sampling technique (N=500) from CoE, GES, NTVI, and other teachers associations. Participants responded to a 30-items, researcher-developed questionnaire. Data is analyzed on the quadrant constructs and reported as ex post facto analyses of multi-variances and regressions. Multiple associations were established for statistical significance (p=0.05). Causes and effects are postulated for scientific discussions. Findings: It was found out that these quadrants are very significant in teacher development. There were significant variations in the demographic groups. However, most teachers lack considerable skills in entrepreneurship, leadership in teaching and learning, and business thinking strategies. These have significant effect on practices and outcomes. Conclusion and Recommendations: It is quite conclusive therefore that in GES teachers may need further instructions in innovations and creativity to transform knowledge-creation into business venture. In service training (INSET) has to be comprehensive. Teacher education curricula at Colleges may have to be re-visited. Teachers have the potential to raise their social capital, to be entrepreneur, and to exhibit professionalism beyond their community services. Their primal leadership focus will benefit many clienteles including students and social circles. Recommendations examined the policy implications for curriculum design, practice, innovations and educational leadership.

Keywords: emotional intelligence, entrepreneurship, leadership, quadrant intelligence (q-i), primal teacher leadership, strategic thinking, social intelligence

Procedia PDF Downloads 315
327 Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines

Authors: Alexander Guzman Urbina, Atsushi Aoyama

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The sustainability of traditional technologies employed in energy and chemical infrastructure brings a big challenge for our society. Making decisions related with safety of industrial infrastructure, the values of accidental risk are becoming relevant points for discussion. However, the challenge is the reliability of the models employed to get the risk data. Such models usually involve large number of variables and with large amounts of uncertainty. The most efficient techniques to overcome those problems are built using Artificial Intelligence (AI), and more specifically using hybrid systems such as Neuro-Fuzzy algorithms. Therefore, this paper aims to introduce a hybrid algorithm for risk assessment trained using near-miss accident data. As mentioned above the sustainability of traditional technologies related with energy and chemical infrastructure constitutes one of the major challenges that today’s societies and firms are facing. Besides that, the adaptation of those technologies to the effects of the climate change in sensible environments represents a critical concern for safety and risk management. Regarding this issue argue that social consequences of catastrophic risks are increasing rapidly, due mainly to the concentration of people and energy infrastructure in hazard-prone areas, aggravated by the lack of knowledge about the risks. Additional to the social consequences described above, and considering the industrial sector as critical infrastructure due to its large impact to the economy in case of a failure the relevance of industrial safety has become a critical issue for the current society. Then, regarding the safety concern, pipeline operators and regulators have been performing risk assessments in attempts to evaluate accurately probabilities of failure of the infrastructure, and consequences associated with those failures. However, estimating accidental risks in critical infrastructure involves a substantial effort and costs due to number of variables involved, complexity and lack of information. Therefore, this paper aims to introduce a well trained algorithm for risk assessment using deep learning, which could be capable to deal efficiently with the complexity and uncertainty. The advantage point of the deep learning using near-miss accidents data is that it could be employed in risk assessment as an efficient engineering tool to treat the uncertainty of the risk values in complex environments. The basic idea of using a Near-Miss Deep Learning Approach for Neuro-Fuzzy Risk Assessment in Pipelines is focused in the objective of improve the validity of the risk values learning from near-miss accidents and imitating the human expertise scoring risks and setting tolerance levels. In summary, the method of Deep Learning for Neuro-Fuzzy Risk Assessment involves a regression analysis called group method of data handling (GMDH), which consists in the determination of the optimal configuration of the risk assessment model and its parameters employing polynomial theory.

Keywords: deep learning, risk assessment, neuro fuzzy, pipelines

Procedia PDF Downloads 292
326 Unveiling Drought Dynamics in the Cuneo District, Italy: A Machine Learning-Enhanced Hydrological Modelling Approach

Authors: Mohammadamin Hashemi, Mohammadreza Kashizadeh

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Droughts pose a significant threat to sustainable water resource management, agriculture, and socioeconomic sectors, particularly in the field of climate change. This study investigates drought simulation using rainfall-runoff modelling in the Cuneo district, Italy, over the past 60-year period. The study leverages the TUW model, a lumped conceptual rainfall-runoff model with a semi-distributed operation capability. Similar in structure to the widely used Hydrologiska Byråns Vattenbalansavdelning (HBV) model, the TUW model operates on daily timesteps for input and output data specific to each catchment. It incorporates essential routines for snow accumulation and melting, soil moisture storage, and streamflow generation. Multiple catchments' discharge data within the Cuneo district form the basis for thorough model calibration employing the Kling-Gupta Efficiency (KGE) metric. A crucial metric for reliable drought analysis is one that can accurately represent low-flow events during drought periods. This ensures that the model provides a realistic picture of water availability during these critical times. Subsequent validation of monthly discharge simulations thoroughly evaluates overall model performance. Beyond model development, the investigation delves into drought analysis using the robust Standardized Runoff Index (SRI). This index allows for precise characterization of drought occurrences within the study area. A meticulous comparison of observed and simulated discharge data is conducted, with particular focus on low-flow events that characterize droughts. Additionally, the study explores the complex interplay between land characteristics (e.g., soil type, vegetation cover) and climate variables (e.g., precipitation, temperature) that influence the severity and duration of hydrological droughts. The study's findings demonstrate successful calibration of the TUW model across most catchments, achieving commendable model efficiency. Comparative analysis between simulated and observed discharge data reveals significant agreement, especially during critical low-flow periods. This agreement is further supported by the Pareto coefficient, a statistical measure of goodness-of-fit. The drought analysis provides critical insights into the duration, intensity, and severity of drought events within the Cuneo district. This newfound understanding of spatial and temporal drought dynamics offers valuable information for water resource management strategies and drought mitigation efforts. This research deepens our understanding of drought dynamics in the Cuneo region. Future research directions include refining hydrological modelling techniques and exploring future drought projections under various climate change scenarios.

Keywords: hydrologic extremes, hydrological drought, hydrological modelling, machine learning, rainfall-runoff modelling

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325 A Lung Cancer Patients with Septic Shock Nursing Experience

Authors: Syue-Wen Lin

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Objective: This article explores the nursing experience of an 84-year-old male lung cancer patient who underwent a thoracoscopic right lower lobectomy and treatment. The patient has multiple medical histories, including hypertension and diabetes. The nursing process involved cancer treatment, postoperative pain management, as well as wound care and healing. Methods: The nursing period is from February 10 to February 17, 2024. During the nursing process, pain management strategies are implemented, including morphine drugs and non-drug methods, and music therapy, essential oil massage, and extended reception time are used to make patients feel physically and mentally comfortable so as to reduce postoperative pain and encourage active participation in rehabilitation. Strict sterile wound dressing procedures and advanced wound care techniques are used to promote wound healing and prevent infection. Due to septic shock, dialysis is used to relieve worsening symptoms. Taking into account the patient's cancer status, the nursing team provides comprehensive cancer care based on the patient's physical and psychological needs. Given the complexity of the patient's condition, including advanced cancer, palliative care is also incorporated throughout the care process to relieve discomfort and provide psychological support. Results: Through comprehensive health assessment, the nursing team fully understood the patient's condition and developed a personalized care plan based on the patient's condition. The interprofessional critical care team provides respiratory therapy and lung expansion exercises to reduce muscle loss while addressing the patient's psychological status, pain management, and vital sign stabilization needs, resulting in a comprehensive approach to care. Lung expansion exercises and the use of a high-frequency chest wall oscillation vest successfully improved sputum drainage and facilitated weaning from mechanical ventilation. In addition, helping patients stabilize their vital signs and the integration of cancer care, pain management, wound care and palliative care helps the patient be fully supported throughout the recovery process, ultimately improving his quality of life. Conclusion: Lung cancer and septic shock present significant challenges to patients, and the nursing team not only provides critical care but also addresses the unique needs of patients through comprehensive infection control, cancer care, pain management, wound care, and palliative care interventions. These measures effectively improve patients' quality of life, promote recovery, and provide compassionate palliative care for terminally ill patients. Nursing staff work closely with family members to develop a comprehensive care plan to ensure that patients receive high-quality medical care as well as psychological support and a comfortable recovery environment.

Keywords: septic shock, lung cancer, palliative care, nursing experience

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324 Participatory Action Research for Sustainability with Special Focus on Student Initiatives

Authors: Soni T. L.

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Sustainable environmental stress is a major concern which needs immediate attention. This paper is an attempt to present participatory action research for sustainable agriculture. Being first and best culture, agriculture protects and improves the natural environment, the social and economic conditions of people, and safeguards the health and welfare of all groups. During course of time agriculture turned to agribusiness, then the values are not safeguarded. Moreover, in today’s busy life many are not taking efforts to take part in agriculture production. Then children are not getting the opportunity to understand agriculture and farming practices. So student initiatives are vital to make them aware. Here the programmes structured by the researcher come under the auspicious of National Service Scheme, a student-centered educational programme, organized by Ministry of Youth Affairs, Government of India. The twin objectives of the study are to examine the role of student initiatives for sustainable agriculture and the role of participatory action research in student initiatives. SWOT analysis is made to study strengths, weaknesses, threats and opportunities. The Methodology adopted is Participatory Action Research. The method is participatory in a sense there is collaboration through participation. The method is action, there is lab land experiences which is real. The method is research that there is documented lessons and creation of new knowledge. Plan of action cover measures adopted and strategies taken i.e., bhavana – kalpana – yojana – sadhana. Through the team effort, the team was successful in converting more than 10 hectares of barren land into cultivable land within and outside the campus. Team efforts of students saved a huge amount of labour cost and produced a huge quantity of organic output and the team was also successful in creating 1000 rain pits in the premises of College for rainwater harvesting. The findings include conveyance of the Message: Food Production is superior to Food donation. Moreover, the study fostered good work ethic and social responsibility among students. Students undertake innovative programmes underlying social and environmental issues and participants got increased opportunities to interact with local and less privileged and acquired increased awareness about real-life experiences which make them confident to interact with people and it resulted in the strengthening of social capital- cooperation, team spirit, social commitment among students. Participants promoted sustainable domestic efforts and ultimately environmental protection is ensured. Finally, there is recognition to the team, institution and the researcher at the university level, state level and at the national level. The learned lessons are, if the approach is good, the response is good and success generates success. Participatory action research is empowering experience for practitioners, focusing the combined time, energy and creativity of a committed group we should lead so many programmes which makes the institution centre of excellence. Authorities should take necessary steps for the Inclusion of community development activities in the curriculum. Action research is problem, client and action centered. So, we must adapt and adopt, coordinates and correlates measures which preserve and conserve the environment.

Keywords: participatory action research, student initiatives, sustainable development, sustainability

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323 Reading and Writing Memories in Artificial and Human Reasoning

Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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322 Lessons Learned through a Bicultural Approach to Tsunami Education in Aotearoa New Zealand

Authors: Lucy H. Kaiser, Kate Boersen

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Kura Kaupapa Māori (kura) and bilingual schools are primary schools in Aotearoa/New Zealand which operate fully or partially under Māori custom and have curricula developed to include Te Reo Māori and Tikanga Māori (Māori language and cultural practices). These schools were established to support Māori children and their families through reinforcing cultural identity by enabling Māori language and culture to flourish in the field of education. Māori kaupapa (values), Mātauranga Māori (Māori knowledge) and Te Reo are crucial considerations for the development of educational resources developed for kura, bilingual and mainstream schools. The inclusion of hazard risk in education has become an important issue in New Zealand due to the vulnerability of communities to a plethora of different hazards. Māori have an extensive knowledge of their local area and the history of hazards which is often not appropriately recognised within mainstream hazard education resources. Researchers from the Joint Centre for Disaster Research, Massey University and East Coast LAB (Life at the Boundary) in Napier were funded to collaboratively develop a toolkit of tsunami risk reduction activities with schools located in Hawke’s Bay’s tsunami evacuation zones. A Māori-led bicultural approach to developing and running the education activities was taken, focusing on creating culturally and locally relevant materials for students and schools as well as giving students a proactive role in making their communities better prepared for a tsunami event. The community-based participatory research is Māori-centred, framed by qualitative and Kaupapa Maori research methodologies and utilizes a range of data collection methods including interviews, focus groups and surveys. Māori participants, stakeholders and the researchers collaborated through the duration of the project to ensure the programme would align with the wider school curricula and kaupapa values. The education programme applied a tuakana/teina, Māori teaching and learning approach in which high school aged students (tuakana) developed tsunami preparedness activities to run with primary school students (teina). At the end of the education programme, high school students were asked to reflect on their participation, what they had learned and what they had enjoyed during the activities. This paper draws on lessons learned throughout this research project. As an exemplar, retaining a bicultural and bilingual perspective resulted in a more inclusive project as there was variability across the students’ levels of confidence using Te Reo and Māori knowledge and cultural frameworks. Providing a range of different learning and experiential activities including waiata (Māori songs), pūrākau (traditional stories) and games was important to ensure students had the opportunity to participate and contribute using a range of different approaches that were appropriate to their individual learning needs. Inclusion of teachers in facilitation also proved beneficial in assisting classroom behavioral management. Lessons were framed by the tikanga and kawa (protocols) of the school to maintain cultural safety for the researchers and the students. Finally, the tuakana/teina component of the education activities became the crux of the programme, demonstrating a path for Rangatahi to support their whānau and communities through facilitating disaster preparedness, risk reduction and resilience.

Keywords: school safety, indigenous, disaster preparedness, children, education, tsunami

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321 Quality Characteristics of Road Runoff in Coastal Zones: A Case Study in A25 Highway, Portugal

Authors: Pedro B. Antunes, Paulo J. Ramísio

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Road runoff is a linear source of diffuse pollution that can cause significant environmental impacts. During rainfall events, pollutants from both stationary and mobile sources, which have accumulated on the road surface, are dragged through the superficial runoff. Road runoff in coastal zones may present high levels of salinity and chlorides due to the proximity of the sea and transported marine aerosols. Appearing to be correlated to this process, organic matter concentration may also be significant. This study assesses this phenomenon with the purpose of identifying the relationships between monitored water quality parameters and intrinsic site variables. To achieve this objective, an extensive monitoring program was conducted on a Portuguese coastal highway. The study included thirty rainfall events, in different weather, traffic and salt deposition conditions in a three years period. The evaluations of various water quality parameters were carried out in over 200 samples. In addition, the meteorological, hydrological and traffic parameters were continuously measured. The salt deposition rates (SDR) were determined by means of a wet candle device, which is an innovative feature of the monitoring program. The SDR, variable throughout the year, appears to show a high correlation with wind speed and direction, but mostly with wave propagation, so that it is lower in the summer, in spite of the favorable wind direction in the case study. The distance to the sea, topography, ground obstacles and the platform altitude seems to be also relevant. It was confirmed the high salinity in the runoff, increasing the concentration of the water quality parameters analyzed, with significant amounts of seawater features. In order to estimate the correlations and patterns of different water quality parameters and variables related to weather, road section and salt deposition, the study included exploratory data analysis using different techniques (e.g. Pearson correlation coefficients, Cluster Analysis and Principal Component Analysis), confirming some specific features of the investigated road runoff. Significant correlations among pollutants were observed. Organic matter was highlighted as very dependent of salinity. Indeed, data analysis showed that some important water quality parameters could be divided into two major clusters based on their correlations to salinity (including organic matter associated parameters) and total suspended solids (including some heavy metals). Furthermore, the concentrations of the most relevant pollutants seemed to be very dependent on some meteorological variables, particularly the duration of the antecedent dry period prior to each rainfall event and the average wind speed. Based on the results of a monitoring case study, in a coastal zone, it was proven that SDR, associated with the hydrological characteristics of road runoff, can contribute for a better knowledge of the runoff characteristics, and help to estimate the specific nature of the runoff and related water quality parameters.

Keywords: coastal zones, monitoring, road runoff pollution, salt deposition

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320 Performance Evaluation of Various Displaced Left Turn Intersection Designs

Authors: Hatem Abou-Senna, Essam Radwan

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With increasing traffic and limited resources, accommodating left-turning traffic has been a challenge for traffic engineers as they seek balance between intersection capacity and safety; these are two conflicting goals in the operation of a signalized intersection that are mitigated through signal phasing techniques. Hence, to increase the left-turn capacity and reduce the delay at the intersections, the Florida Department of Transportation (FDOT) moves forward with a vision of optimizing intersection control using innovative intersection designs through the Transportation Systems Management & Operations (TSM&O) program. These alternative designs successfully eliminate the left-turn phase, which otherwise reduces the conventional intersection’s (CI) efficiency considerably, and divide the intersection into smaller networks that would operate in a one-way fashion. This study focused on the Crossover Displaced Left-turn intersections (XDL), also known as Continuous Flow Intersections (CFI). The XDL concept is best suited for intersections with moderate to high overall traffic volumes, especially those with very high or unbalanced left turn volumes. There is little guidance on determining whether partial XDL intersections are adequate to mitigate the overall intersection condition or full XDL is always required. The primary objective of this paper was to evaluate the overall intersection performance in the case of different partial XDL designs compared to a full XDL. The XDL alternative was investigated for 4 different scenarios; partial XDL on the east-west approaches, partial XDL on the north-south approaches, partial XDL on the north and east approaches and full XDL on all 4 approaches. Also, the impact of increasing volume on the intersection performance was considered by modeling the unbalanced volumes with 10% increment resulting in 5 different traffic scenarios. The study intersection, located in Orlando Florida, is experiencing recurring congestion in the PM peak hour and is operating near capacity with volume to a capacity ratio closer to 1.00 due to the presence of two heavy conflicting movements; southbound and westbound. The results showed that a partial EN XDL alternative proved to be effective and compared favorably to a full XDL alternative followed by the partial EW XDL alternative. The analysis also showed that Full, EW and EN XDL alternatives outperformed the NS XDL and the CI alternatives with respect to the throughput, delay and queue lengths. Significant throughput improvements were remarkable at the higher volume level with percent increase in capacity of 25%. The percent reduction in delay for the critical movements in the XDL scenarios compared to the CI scenario ranged from 30-45%. Similarly, queue lengths showed percent reduction in the XDL scenarios ranging from 25-40%. The analysis revealed how partial XDL design can improve the overall intersection performance at various demands, reduce the costs associated with full XDL and proved to outperform the conventional intersection. However, partial XDL serving low volumes or only one of the critical movements while other critical movements are operating near or above capacity do not provide significant benefits when compared to the conventional intersection.

Keywords: continuous flow intersections, crossover displaced left-turn, microscopic traffic simulation, transportation system management and operations, VISSIM simulation model

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319 Monitoring and Improving Performance of Soil Aquifer Treatment System and Infiltration Basins of North Gaza Emergency Sewage Treatment Plant as Case Study

Authors: Sadi Ali, Yaser Kishawi

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As part of Palestine, Gaza Strip (365 km2 and 1.8 million habitants) is considered a semi-arid zone relies solely on the Coastal Aquifer. The coastal aquifer is only source of water with only 5-10% suitable for human use. This barely covers the domestic and agricultural needs of Gaza Strip. Palestinian Water Authority Strategy is to find non-conventional water resource from treated wastewater to irrigate 1500 hectares and serves over 100,000 inhabitants. A new WWTP project is to replace the old-overloaded Biet Lahia WWTP. The project consists of three parts; phase A (pressure line & 9 infiltration basins - IBs), phase B (a new WWTP) and phase C (Recovery and Reuse Scheme – RRS – to capture the spreading plume). Currently, phase A is functioning since Apr 2009. Since Apr 2009, a monitoring plan is conducted to monitor the infiltration rate (I.R.) of the 9 basins. Nearly 23 million m3 of partially treated wastewater were infiltrated up to Jun 2014. It is important to maintain an acceptable rate to allow the basins to handle the coming quantities (currently 10,000 m3 are pumped an infiltrated daily). The methodology applied was to review and analysis the collected data including the I.R.s, the WW quality and the drying-wetting schedule of the basins. One of the main findings is the relation between the Total Suspended Solids (TSS) at BLWWTP and the I.R. at the basins. Since April 2009, the basins scored an average I.R. of about 2.5 m/day. Since then the records showed a decreasing pattern of the average rate until it reached the lower value of 0.42 m/day in Jun 2013. This was accompanied with an increase of TSS (mg/L) concentration at the source reaching above 200 mg/L. The reducing of TSS concentration directly improved the I.R. (by cleaning the WW source ponds at Biet Lahia WWTP site). This was reflected in an improvement in I.R. in last 6 months from 0.42 m/day to 0.66 m/day then to nearly 1.0 m/day as the average of the last 3 months of 2013. The wetting-drying scheme of the basins was observed (3 days wetting and 7 days drying) besides the rainfall rates. Despite the difficulty to apply this scheme accurately a control of flow to each basin was applied to improve the I.R. The drying-wetting system affected the I.R. of individual basins, thus affected the overall system rate which was recorded and assessed. Also the ploughing activities at the infiltration basins as well were recommended at certain times to retain a certain infiltration level. This breaks the confined clogging layer which prevents the infiltration. It is recommended to maintain proper quality of WW infiltrated to ensure an acceptable performance of IBs. The continual maintenance of settling ponds at BLWWTP, continual ploughing of basins and applying soil treatment techniques at the IBs will improve the I.R.s. When the new WWTP functions a high standard effluent quality (TSS 20mg, BOD 20 mg/l, and TN 15 mg/l) will be infiltrated, thus will enhance I.R.s of IBs due to lower organic load.

Keywords: soil aquifer treatment, recovery and reuse scheme, infiltration basins, North Gaza

Procedia PDF Downloads 247