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Authors: Sarah Elshahat, Tina Moffat

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Suboptimal mental health is a considerable global public health challenge that leads to considerable inequalities worldwide. Newcomers are at elevated risk for developing mental health issues as a result of social exclusion, stigmatization, racism, unequal employment opportunities, and discrimination. The problem can be especially serious amongst Arabic-speaking immigrants and refugees (ASIR) whose mental wellness may have already been affected by exposure to political violence, persecution, hunger or war in their countries of origin. A scoping review was conducted to investigate pre- and post-migration mental health determinants amongst ASIR in North America (the U.S. and Canada), who are a rapidly growing population in both regions. Pertinent peer-reviewed papers and grey literature were located through a systematic search of five electronic databases (Medline, Embase, PsycINFO, Anthropology Plus, and Sociology Database). A stakeholder consultation was implemented to validate the analyzed findings of the included 44 studies. About 80% of the studies were carried out in the US, underscoring a lack of Canadian ASIR-mental health research. A gap in qualitative, mixed-method, and longitudinal research was detected, where approximately two-thirds of the studies adopted a cross-sectional method. Pre-migration determinants of mental health were related to the political unrest, violence and armed conflict in the Arab world, increasing post-traumatic stress disorder and psychological distress levels among ASIR. English language illiteracy and generational variations in acculturation patterns were major post-migration mental health triggering factors. Exposure to domestic violence, stigmatization, poverty, racialization, and harassment were significant post-migration mental health determinants that stem from social inequalities, triggering depression, and distress amongst ASIR. Family conflicts linked to child-rearing and gendered norms were considered as both pre- and post-migration mental health triggering factors. Most post-migration mental health protective factors were socio-culturally related and included the maintenance of positive ethnic identity, faith, family support, and community cohesion. Individual resilience, articulated as self-esteem and hope, was a significant negative predictor of depression and psychological distress among ASIR. Community-engaged, mixed-methods, and longitudinal studies are required to address the current gap in mental health research among ASIR in North America. A more thorough determination of potential mental health triggers and protective factors would help inform the development of mental wellness and resilience-promoting programs that are culturally sensitive to ASIR. On the policy level, the Health in All Policies framework of the World Health Organization can be potentially useful for addressing social and health inequalities among ASIR, reducing mental health challenges.

Keywords: depression, post-traumatic stress disorder, psychological distress, resilience

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Authors: X. Simon, D. Copena, M. Montero

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The last decades have witnessed a significant increase in renewable energy, especially wind energy, to achieve sustainable development. Specialized literature in this field has carried out interesting case studies to extensively analyze both the environmental benefits of this energy and its social acceptance. However, to the best of our knowledge, work to date makes no analysis of the role of private owners of lands with wind potential within a broader territory of strong wind implantation, nor does it estimate their economic incomes relating them to social acceptance. This work fills this gap by focusing on Galicia, territory housing over 4,000 wind turbines and almost 3,400 MW of power. The main difficulty in getting this financial information is that it is classified, not public. We develop methodological techniques (semi- structured interviews and work groups), inserted within the Participatory Research, to overcome this important obstacle. In this manner, the work directly compiles qualitative and quantitative information on the processes as well as the economic results derived from implementing wind energy in Galicia. During the field work, we held 106 semi-structured interviews and 32 workshops with owners of lands occupied by wind farms. The compiled information made it possible to create the socioeconomic database on wind energy in Galicia (SDWEG). This database collects a diversity of quantitative and qualitative information and contains economic information on the income received by the owners of lands occupied by wind farms. In the Galician case, regulatory framework prevented local participation under the community wind farm formula. The possibility of local participation in the new energy model narrowed down to companies wanting to install a wind farm and demanding land occupation. The economic mechanism of local participation begins here, thus explaining the level of acceptance of wind farms. Land owners can receive significant income given that these payments constitute an important source of economic resources, favor local economic activity, allow rural areas to develop productive dynamism projects and improve the standard of living of rural inhabitants. This work estimates that land owners in Galicia perceive about 10 million euros per year in total wind revenues. This represents between 1% and 2% of total wind farm invoicing. On the other hand, relative revenues (Euros per MW), far from the amounts reached in other spaces, show enormous payment variability. This signals the absence of a regulated market, the predominance of partial agreements, and the existence of asymmetric positions between owners and developers. Sustainable development requires the replacement of conventional technologies by low environmental impact technologies, especially those that emit less CO₂. However, this new paradigm also requires rural owners to participate in the income derived from the structural transformation processes linked to sustainable development. This paper demonstrates that regulatory framework may contribute to increasing sustainable technologies with high social acceptance without relevant local economic participation.

Keywords: regulatory framework, social acceptance, sustainable development, wind energy, wind income for landowners

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Authors: komal verma, V. S. Moholkar

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In this current study, the challenge of effectively treating and mineralizing industrial wastewater prior to its discharge into natural water bodies, such as rivers and lakes, is being addressed. Particularly, the focus is on the wastewater produced by chemical process industries, including refineries, petrochemicals, fertilizer, pharmaceuticals, pesticides, and dyestuff industries. These wastewaters often contain stubborn organic pollutants that conventional techniques, such as microbial processes cannot efficiently degrade. To tackle this issue, a ternary hybrid technique comprising of adsorption, heterogeneous Fenton process, and sonication has been employed. The study aims to evaluate the effectiveness of this approach for treating and mineralizing wastewater from a fertilizer industry located in Northeast India. The study comprises several key components, starting with the synthesis of the Fe3O4@AC nanocomposite using the co-precipitation method. The nanocomposite is then subjected to comprehensive characterization through various standard techniques, including FTIR, FE-SEM, EDX, TEM, BET surface area analysis, XRD, and magnetic property determination using VSM. Next, the process parameters of wastewater treatment are statistically optimized, focusing on achieving a high level of COD (Chemical Oxygen Demand) removal as the response variable. The Fe3O4@AC nanocomposite's adsorption characteristics and kinetics are also assessed in detail. The remarkable outcome of this study is the successful application of the ternary hybrid technique, combining adsorption, Fenton process, and sonication. This approach proves highly effective, leading to nearly complete mineralization (or TOC removal) of the fertilizer industry wastewater. The results highlight the potential of the Fe3O4@AC nanocomposite and the ternary hybrid technique as a promising solution for tackling challenging wastewater pollutants from various chemical process industries. This paper reports investigations in the mineralization of industrial wastewater (COD = 3246 mg/L, TOC = 2500 mg/L) using a ternary (ultrasound + Fenton + adsorption) hybrid advanced oxidation process. Fe3O4 decorated activated charcoal (Fe3O4@AC) nanocomposites (surface area = 538.88 m2/g; adsorption capacity = 294.31 mg/g) were synthesized using co-precipitation. The wastewater treatment process was optimized using central composite statistical design. At optimum conditions, viz. pH = 4.2, H2O2 loading = 0.71 M, adsorbent dose = 0.34 g/L, reduction in COD and TOC of wastewater were 94.75% and 89%, respectively. This result results from synergistic interactions among the adsorption of pollutants onto activated charcoal and surface Fenton reactions induced due to the leaching of Fe2+/Fe3+ ions from the Fe3O4 nanoparticles. Micro-convection generated due to sonication assisted faster mass transport (adsorption/desorption) of pollutants between Fe3O4@AC nanocomposite and the solution. The net result of this synergism was high interactions and reactions among and radicals and pollutants that resulted in the effective mineralization of wastewater. The Fe3O4@AC showed excellent recovery (> 90 wt%) and reusability (> 90% COD removal) in 5 successive cycles of treatment. LC-MS analysis revealed effective (> 50%) degradation of more than 25 significant contaminants (in the form of herbicides and pesticides) after the treatment with ternary hybrid AOP. Similarly, the toxicity analysis test using the seed germination technique revealed ~ 60% reduction in the toxicity of the wastewater after treatment.

Keywords: chemical oxygen demand (cod), fe3o4@ac nanocomposite, kinetics, lc-ms, rsm, toxicity

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Authors: Rohit T. P., Sahil Athrij, Sasi Gopalan

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Currently, the content entertainment industry is dominated by mobile devices. As the trends slowly shift towards Augmented/Virtual Reality applications the computational demands on these devices are increasing exponentially and we are already reaching the limits of hardware optimizations. This paper proposes a software solution to this problem. By leveraging the capabilities of cloud computing we can offload the work from mobile devices to dedicated rendering servers that are way more powerful. But this introduces the problem of latency. This paper introduces a protocol that can achieve high-performance low latency Augmented/Virtual Reality experience. There are two parts to the protocol, 1) In-flight compression The main cause of latency in the system is the time required to transmit the camera frame from client to server. The round trip time is directly proportional to the amount of data transmitted. This can therefore be reduced by compressing the frames before sending. Using some standard compression algorithms like JPEG can result in minor size reduction only. Since the images to be compressed are consecutive camera frames there won't be a lot of changes between two consecutive images. So inter-frame compression is preferred. Inter-frame compression can be implemented efficiently using WebGL but the implementation of WebGL limits the precision of floating point numbers to 16bit in most devices. This can introduce noise to the image due to rounding errors, which will add up eventually. This can be solved using an improved interframe compression algorithm. The algorithm detects changes between frames and reuses unchanged pixels from the previous frame. This eliminates the need for floating point subtraction thereby cutting down on noise. The change detection is also improved drastically by taking the weighted average difference of pixels instead of the absolute difference. The kernel weights for this comparison can be fine-tuned to match the type of image to be compressed. 2) Dynamic Load distribution Conventional cloud computing architectures work by offloading as much work as possible to the servers, but this approach can cause a hit on bandwidth and server costs. The most optimal solution is obtained when the device utilizes 100% of its resources and the rest is done by the server. The protocol balances the load between the server and the client by doing a fraction of the computing on the device depending on the power of the device and network conditions. The protocol will be responsible for dynamically partitioning the tasks. Special flags will be used to communicate the workload fraction between the client and the server and will be updated in a constant interval of time ( or frames ). The whole of the protocol is designed so that it can be client agnostic. Flags are available to the client for resetting the frame, indicating latency, switching mode, etc. The server can react to client-side changes on the fly and adapt accordingly by switching to different pipelines. The server is designed to effectively spread the load and thereby scale horizontally. This is achieved by isolating client connections into different processes.

Keywords: 2D kernelling, augmented reality, cloud computing, dynamic load distribution, immersive experience, mobile computing, motion tracking, protocols, real-time systems, web-based augmented reality application

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Authors: Khulud Alhussain, Anna Gavine, Stephen Macgillivray, Sushila Chowdhry

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Background: Estimates show that by the year 2030, mental illness will account for more than half of the global economic burden, second to non-communicable diseases. Often, the perinatal period is characterised by psychological ambivalence and a mixed anxiety-depressive condition. Maternal mental disorder is associated with perinatal anxiety and depression and affects breastfeeding behaviors. Studies also indicate that maternal mental health can considerably influence a baby's health in numerous aspects and impact the newborn health due to lack of adequate breastfeeding. However, studies reporting factors associated with breastfeeding behaviors are predominantly quantitative. Therefore, it is not clear what literature is available to understand the factors affecting breastfeeding and perinatal women’s perspectives and experiences. Aim: This review aimed to explore the perceptions and experiences of women with perinatal anxiety and depression, as well as how these experiences influence their breastfeeding behaviours. Methods: A systematic literature review of qualitative studies in line with the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ). Four electronic databases (CINAHL, PsycINFO, Embase, and Google Scholar) were explored for relevant studies using a search strategy. The search was restricted to studies published in the English language between 2000 and 2022. Findings from the literature were screened using a pre-defined screening criterion and the quality of eligible studies was appraised using the Walsh and Downe (2006) checklist. Findings were extracted and synthesised based on Braun and Clark. The review protocol was registered on PROSPERO (Ref: CRD42022319609). Result: A total of 4947 studies were identified from the four databases. Following duplicate removal and screening 16 studies met the inclusion criteria. The studies included 87 pregnant and 302 post-partum women from 12 countries. The participants were from a variety of economic, regional, and religious backgrounds, mainly from the age of 18 to 45 years old. Three main themes were identified: Barriers to breastfeeding, breastfeeding facilitators, emotional disturbance, and breastfeeding. Seven subthemes emerged from the data: expectation versus reality, uncertainly about maternal competencies, body image and breastfeeding, lack of sufficient breastfeeding support for family and caregivers’ support, influences positive breastfeeding practices, breastfeeding education, and causes of mental strain among breastfeeding women. Breastfeeding duration is affected in women with mental health disorders, irrespective of their desire to breastfeed. Conclusion: There is significant empirical evidence that breastfeeding behaviour and perinatal mental disturbance are linked. However, there is a lack of evidence to apply the findings to Saudi women due to lack of empirical qualitative information. To improve the psychological well-being of mothers, it is crucial to explore and recognise any concerns with their mental, physical, and emotional well-being. Therefore, robust research is needed so that breastfeeding intervention researchers and policymakers can focus on specifically what needs to be done to help mentally distressed perinatal women and their new-born.

Keywords: pregnancy, perinatal period, anxiety, depression, emotional disturbance, breastfeeding

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Authors: Samuel McLennan, Tane Moleta, Andre Brown, Marc Aurel Schnabel

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The development of Ecclesiastical buildings within New Zealand has produced some unique design characteristics that take influence from both international styles and local building methods. What this research looks at is how procedural modelling can be used to define such common characteristics and understand how they are shared and developed within different examples of a similar architectural style. This will be achieved through the creation of procedural digital reconstructions of the various timber Gothic Churches built during the 19th century in the city of Wellington, New Zealand. ‘Procedural modelling’ is a digital modelling technique that has been growing in popularity, particularly within the game and film industry, as well as other fields such as industrial design and architecture. Such a design method entails the creation of a parametric ‘ruleset’ that can be easily adjusted to produce many variations of geometry, rather than a single geometry as is typically found in traditional CAD software. Key precedents within this area of digital heritage includes work by Haegler, Müller, and Gool, Nicholas Webb and Andre Brown, and most notably Mark Burry. What these precedents all share is how the forms of the reconstructed architecture have been generated using computational rules and an understanding of the architects’ geometric reasoning. This is also true within this research as Gothic architecture makes use of only a select range of forms (such as the pointed arch) that can be accurately replicated using the same standard geometric techniques originally used by the architect. The methodology of this research involves firstly establishing a sample group of similar buildings, documenting the existing samples, researching any lost samples to find evidence such as architectural plans, photos, and written descriptions, and then culminating all the findings into a single 3D procedural asset within the software ‘Houdini’. The end result will be an adjustable digital model that contains all the architectural components of the sample group, such as the various naves, buttresses, and windows. These components can then be selected and arranged to create visualisations of the sample group. Because timber gothic churches in New Zealand share many details between designs, the created collection of architectural components can also be used to approximate similar designs not included in the sample group, such as designs found beyond the Wellington Region. This creates an initial library of architectural components that can be further expanded on to encapsulate as wide of a sample size as desired. Such a methodology greatly improves upon the efficiency and adjustability of digital modelling compared to current practices found in digital heritage reconstruction. It also gives greater accuracy to speculative design, as a lack of evidence for lost structures can be approximated using components from still existing or better-documented examples. This research will also bring attention to the cultural significance these types of buildings have within the local area, addressing the public’s general unawareness of architectural history that is identified in the Wellington based research ‘Moving Images in Digital Heritage’ by Serdar Aydin et al.

Keywords: digital forensics, digital heritage, gothic architecture, Houdini, procedural modelling

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Authors: Walter E. Allen, Robert D. Murray

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Many large transit agencies have adopted RFID technology and electronic automatic fare collection (AFC) or smart card systems, but small and rural agencies remain tied to obsolete manual, cash-based fare collection. Small countries or transit agencies can benefit from the implementation of smart card AFC technology with the promise of increased passenger convenience, added passenger satisfaction and improved agency efficiency. For transit agencies, it reduces revenue loss, improves passenger flow and bus stop data. For countries, further implementation into security, distribution of social services or currency transactions can provide greater benefits. However, small countries or transit agencies cannot afford expensive proprietary smart card solutions typically offered by the major system suppliers. Deployment of Contactless Fare Media System (CFMS) Standard eliminates the proprietary solution, ultimately lowering the cost of implementation. Acumen Building Enterprise, Inc. chose the Yuma County Intergovernmental Public Transportation Authority (YCIPTA) existing proprietary YCAT smart card system to implement CFMS. The revised system enables the purchase of fare product online with prepaid debit or credit cards using the Payment Gateway Processor. Open and interoperable smart card standards for transit have been developed. During the 90-day Pilot Operation conducted, the transit agency gathered the data from the bus AcuFare 200 Card Reader, loads (copies) the data to a USB Thumb Drive and uploads the data to the Acumen Host Processing Center for consolidation of the data into the transit agency master data file. The transition from the existing proprietary smart card data format to the new CFMS smart card data format was transparent to the transit agency cardholders. It was proven that open standards and interoperability design can work and reduce both implementation and operational costs for small transit agencies or countries looking to expand smart card technology. Acumen was able to avoid the implementation of the Payment Card Industry (PCI) Data Security Standards (DSS) which is expensive to develop and costly to operate on a continuing basis. Due to the substantial additional complexities of implementation and the variety of options presented to the transit agency cardholder, Acumen chose to implement only the Directed Autoload. To improve the implementation efficiency and the results for a similar undertaking, it should be considered that some passengers lack credit cards and are averse to technology. There are more than 1,300 small and rural agencies in the United States. This grows by 10 fold when considering small countries or rural locations throughout Latin American and the world. Acumen is evaluating additional countries, sites or transit agency that can benefit from the smart card systems. Frequently, payment card systems require extensive security procedures for implementation. The Project demonstrated the ability to purchase fare value, rides and passes with credit cards on the internet at a reasonable cost without highly complex security requirements.

Keywords: automatic fare collection, near field communication, small transit agencies, smart cards

Procedia PDF Downloads 282

Authors: Sugam Kale, Arif Uzair Bin Mohammed Roslan, Cindy Lee, Syed Beevee Mohammed Ismail

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Preemptive analgesia is an established concept in the modern practice of anaesthesia. To be most effective, it is best instituted earlier than the surgical stimulus and should last beyond the offset of surgically induced pain till healing is complete. Whereas the start of afferent pain blockade with regional anaesthesia is common, its effect often falls short to cover the entire period of pain impulses making their way to CNS in the post-operative period. We tried to use a combination of two regional anaesthetic techniques used sequentially to overcome this handicap. Madam S., a 56 year old lady, was scheduled for elective surgery for pancreatic cancer. She underwent laparotomy and distal pancreatectomy, splenectomy, bilateral salpingo oophorectomy, and sigmoid colectomy. Surgery was expected to be extensive, and it was presumed that the standard pain relief with PCA with opiates and oral analgesics would not be adequate. After counselling the patient pre-operative about the technique of regional anaesthesia techniques, including epidural catheterization and rectus sheath catheter placement, their benefits, and potential complications, informed consent was obtained. Epidural catheter was placed awake, and general anaesthesia was then induced. Epidural infusion of local anaesthetics was started prior to surgical incision and was continued till 60 hours into the postoperative period. Before skin closure, the surgeons inserted commercially available rectus sheath catheters bilaterally along the midline incision used for laparotomy. After 46 hours post-op, local anaesthetic infusion via these was started as bridging while the epidural infusion rate was tapered off. The epidural catheter was removed at 75 hours. Elastomeric pumps were used to provide local anaesthetic infusion with the ability to vary infusion rates. Acute pain service followed up the patient’s vital signs and effectiveness of pain relief twice daily or more frequently as required. Rectus sheath catheters were removed 137 hours post-op. The patient had good post-op analgesia with the minimal additional analgesic requirement. For the most part, the visual analog score (VAS) for pain remained at 1-3 on a scale of 1 to 10. Haemodynamics remained stable, and surgical recovery was as expected. Minimal opiate requirement after an extensive laparotomy also translates to the early return of intestinal motility. Our experience was encouraging, and we are hoping to extend this combination of two regional anaesthetic techniques to patients undergoing similar surgeries. Epidural analgesia is denser and offers excellent pain relief for both visceral and somatic pain in the first few days after surgery. As the pain intensity grows weaker, rectus sheath block and oral analgesics provide almost the same degree of pain relief after the epidural catheter is removed. We discovered that the background infusion of local anaesthetic down the rectus sheath catherter largely reduced the requirement for other classes of analgesics. We aim to study this further with a larger patient cohort and hope that it may become an established clinical practice that benefits patients everywhere.

Keywords: rectus sheath, epidural infusion, post operative analgesia, elastomeric

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Authors: Julia Wimmers Klick

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Interprofessional Education (IPE) is widely recognized as a valuable approach in healthcare education, despite the challenges it presents. This study explores IP surface anatomy lab sessions, with a focus on fostering trust and collaboration among healthcare students. The research is conducted within the context of rural healthcare settings in British Columbia (BC), where a medical school and a physical therapy (PT) program operate under the Faculty of Medicine at the University of British Columbia (UBC). While IPE sessions addressing soft skills have been implemented, the integration of hard skills, such as Anatomy, remains limited. To address this gap, a pilot feasibility study was conducted with a positive outcome, a follow-up study involved these IPE sessions aimed at exploring the influence of bonding and trust between medical and PT students. Data were collected through focus groups comprising participating students and faculty members, and a structured SWOC (Strengths, Weaknesses, Opportunities, and Challenges) analysis was conducted. The IPE sessions, 3 in total, consisted of a 2.5-hour lab on surface anatomy, where PT students took on the teaching role, and medical students were newly exposed to surface anatomy. The focus of the study was on the relationship-building process and trust development between the two student groups, rather than assessing the acquisition of surface anatomy skills. Results indicated that the surface anatomy lab served as a suitable tool for the application and learning of soft skills. Faculty members observed positive outcomes, including productive interaction between students, reversed hierarchy with PT students teaching medical students, practicing active listening skills, and using a mutual language of anatomy. Notably, there was no grade assessment or external pressure to perform. The students also reported an overall positive experience; however, the specific impact on the development of soft skill competencies could not be definitively determined. Participants expressed a sense of feeling respected, welcomed, and included, all of which contributed to feeling safe. Within the small group environment, students experienced becoming a part of a community of healthcare providers that bonded over a shared interest in health professions education. They enjoyed sharing diverse experiences related to learning across their varied contexts, without fear of judgment and reprisal that were often intimidating in single professional contexts. During a joint Christmas party for both cohorts, faculty members observed students mingling, laughing, and forming bonds. This emphasized the importance of early bonding and trust development among healthcare colleagues, particularly in rural settings. In conclusion, the findings emphasize the potential of IPE sessions to enhance trust and collaboration among healthcare students, with implications for their future professional lives in rural settings. Early bonding and trust development are crucial in rural settings, where healthcare professionals often rely on each other. Future research should continue to explore the impact of content-concentrated IPE on the development of soft skill competencies.

Keywords: interprofessional education, rural healthcare settings, trust, surface anatomy

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Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

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Authors: Jessica M. Black

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Although much of natural and social science research aims to enhance human flourishing and address social problems, the training within the two fields is significantly different across theory, methodology, and implementation of results. Social scientists are trained in social, psychological, and to the extent that it is relevant to their discipline, spiritual development, theory, and accompanying methodologies. They tend not to receive training or learn about accompanying methodology related to interrogating human development and social problems from a biological perspective. On the other hand, those in the natural sciences, and for the purpose of this work, human biological sciences specifically – biology, neuroscience, genetics, epigenetics, and physiology – are often trained first to consider cellular development and related methodologies, and may not have opportunity to receive formal training in many of the foundational principles that guide human development, such as systems theory or person-in-environment framework, methodology related to tapping both proximal and distal psycho-social-spiritual influences on human development, and foundational principles of equity, justice and inclusion in research design. There is a need for disciplines heretofore siloed to know one another, to receive streamlined, easy to access training in theory and methods from one another and to learn how to build interdisciplinary teams that can speak and act upon a shared research language. Team science is more essential than ever, as are transdisciplinary approaches to training and research design. This study explores the use of a methodological toolbox that natural and social scientists can use by employing a decision-making tree regarding project aims, costs, and participants, among other important study variables. The decision tree begins with a decision about whether the researcher wants to learn more about social sciences approaches or biological approaches to study design. The toolbox and platform are flexible, such that users could also choose among modules, for instance, reviewing epigenetics or community-based participatory research even if those are aspects already a part of their home field. To start, both natural and social scientists would receive training on systems science, team science, transdisciplinary approaches, and translational science. Next, social scientists would receive training on grounding biological theory and the following methodological approaches and tools: physiology, (epi)genetics, non-invasive neuroimaging, invasive neuroimaging, endocrinology, and the gut-brain connection. Natural scientists would receive training on grounding social science theory, and measurement including variables, assessment and surveys on human development as related to the developing person (e.g., temperament and identity), microsystems (e.g., systems that directly interact with the person such as family and peers), mesosystems (e.g., systems that interact with one another but do not directly interact with the individual person, such as parent and teacher relationships with one another), exosystems (e.g., spaces and settings that may come back to affect the individual person, such as a parent’s work environment, but within which the individual does not directly interact, macrosystems (e.g., wider culture and policy), and the chronosystem (e.g., historical time, such as the generational impact of trauma). Participants will be able to engage with the toolbox and one another to foster increased transdisciplinary work

Keywords: methodology, natural science, social science, transdisciplinary

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Authors: Timothy Gray

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This paper will present work and discuss lessons learned during a semester-long travel study based in Southeast Asia, which was run in the Spring Semester of 2019 and again in the summer of 2023. The first travel group consisted of fifteen students, and the second group consisted of twelve students ranging from second-year to graduate level, student participants majoring in either architecture or planning. Students worked in interdisciplinary teams, each team beginning their travel study, living together in a separate small town for over a month in (relatively) remote conditions in rural Thailand. Students became intimately familiar with these towns, forged strong personal relationships, and built reservoirs of knowledge one conversation at a time. Rather than impose external ideas and solutions, students were asked to learn from and be open to lessons from the people and the place. The following design statement was used as a point of departure for their investigations: It is our shared premise that architecture exists in small villages and towns of Southeast Asia in the ingenuity of the people, that architecture exists in a shared language of making, modifying, and reusing. It is a modest but vibrant architecture, an architecture that is alive and evolving, an architecture that is small in scale, accessible, and one that emerges from the people. It is an architecture that can exist in a modified bicycle, a woven bamboo bridge, or a self-built community. Students were challenged to engage in existing conditions as design professionals, both empowering and lending coherence to the energies that already existed in the place. As one of the student teams noted in their design narrative: “During our field study, we had the unique opportunity to tour a number of informal settlements and meet and talk to residents through interpreters. We found that many of the residents work in nearby factories for dollars a day. Others find employment in self-generated informal economies such as hand carving and textiles. Despite extreme poverty, we found these places to be vibrant and full of life as people navigate these challenging conditions to live lives with purpose and dignity.” Students worked together with local community members and colleagues to develop a series of varied proposals that emerged from their interrogations of place and partnered with community members and professional colleagues in the development of these proposals. Project partners included faculty and student colleagues Yangon University, the mayor's Office, Planning Department Officials and religious leaders in Sawankhalok, Thailand, and community leaders in Natonchan, Thailand, to name a few. This paper will present a series of student community-based design projects that emerged from these conditions. The paper will also discuss this model of travel study as a way of building an architecture which uses social and cultural issues as a catalyst for design. The paper will discuss lessons relative to sustainable development that the Western students learned through their travels in Southeast Asia.

Keywords: travel study, CAPasia, architecture of empowerment, modular housing

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Shawn Baker-Garcia, Janna O. Schaeffer

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As the global and national communities and governments strive to address ongoing and evolving threats to humanity and pervasive or emerging “shared” global priorities on environmental, economic, political, and security, it is more urgent than ever before to understand each other, communicate effectively with one another, identify models of cooperation that yield improved, mutually reinforcing outcomes across and within cultures. It is within the backdrop of this reality that the presentation examines whether cultural training as we have approached it in recent decades is sufficiently meeting our current needs and what changes may be applied to foster better and more productive and sustainable intercultural interactions. Domestic and global relations face multiple challenges to peaceable cooperation. The last two years, in particular, have been defined by a travel-restricted COVID-19 pandemic yielding increased intercultural interactions over virtual platforms, polarized politics dividing nations and regions, and the commensurate rise in weaponized social and traditional media communication. These societal and cultural fissures are noticeably challenging our collective and individual abilities to constructively interact both at home and abroad. It is within this pressure cooker environment that the authors believe it is time to reexamine existing and broadly accepted inter- and cross- cultural training approaches and concepts to determine their level of effectiveness in setting conditions for optimal human understanding and relationships both in the national and international context. In order to better understand the amount and the type of intercultural training practitioners professionally engaging in international partnership building have received throughout their careers and its perceived effectiveness, a survey was designed and distributed to US and international professionals presently engaged in the fields of diplomacy, military, academia, and international business. The survey questions were deigned to address the two primary research questions investigators posed in this exploratory study. Research questions aimed to examine practitioners’ view of the role and effectiveness of current and traditional cultural training and education as a means to fostering improved communication, interactions, understanding, and cooperation among inter, cross, or multi-cultural communities or efforts.Responses were then collected and analyzed for themes present in the participants’ reflections. In their responses, the practitioners identified the areas of improvement and desired outcomes in regards to intercultural training and awareness raising curricular approaches. They also raised issues directly and indirectly pertaining to the role of foreign language proficiency in intercultural interactions and a need for a solid grasp on cultural and regional issues (regional expertise) to facilitate such an interaction. Respondents indicated knowledge, skills, abilities, and capabilities that the participants were not trained on but learned through ad hoc personal and professional intercultural interactions, which they found most valuable and wished they had acquired prior to the intercultural experience.

Keywords: cultural training, improved communication, intercultural competence, international cooperation

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Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, a new set of metrics and measurement system is needed to better quantify the environmental, social and economic impacts of circular zero-waste design. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. Lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. In particular, the forestry-based plants which have been an invaluable outlet for woody biomass surplus, forest health improvement, timber production enhancement, and especially reduction of wildfire risk. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. It proposes not only models for integration of forestry, aquaculture, and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. Typically, life cycle analyses measure environmental impacts of different industrial production stages and are not integrated with indicators of material use circularity. This concept paper proposes the further development of a new set of metrics that would illustrate not only the typical life-cycle analysis (LCA), which shows the reduction in greenhouse gas (GHG) emissions, but also the zero-waste circularity measures of mass balance of the full value chain of the raw material and energy content/caloric value. These new measures quantify key impacts in making hyper-efficient use of natural resources and eliminating waste to landfills. The project utilized traditional LCA using the GREET model where the standalone biomass energy plant case was contrasted with the integration of a jet-fuel biorefinery. The methodology was then expanded to include combinations of co-hosts that optimize the life cycle of woody biomass from tree to energy, CO₂, heat and wood ash both from an energy/caloric value and for mass balance to include reuse of waste streams which are typically landfilled. The major findings of both a formal LCA study resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. If proven as a model, the expedited roll-out of these innovative scenarios can set a new standard for circular zero-waste projects that advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable bio-economy paradigm where waste streams become valuable inputs, supporting local and rural communities in simple, sustainable ways.

Keywords: bio-economy, biomass energy, financing, metrics

Procedia PDF Downloads 155

Authors: Solanki Ravirajsinh, Kudo Kuniaki, Sharma Ankit, Devi Sherine, Kuboshima Misaki, Tachi Shuntaro

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In software development life cycles, the absence of scalable CI/CD significantly impacts organizations, leading to increased overall maintenance costs, prolonged release delivery times, heightened manual efforts, and difficulties in meeting tight deadlines. Implementing CI/CD with standard serverless technologies using cloud services overcomes all the above-mentioned issues and helps organizations improve efficiency and faster delivery without the need to manage server maintenance and capacity. By integrating scalable CI/CD with scalable automation testing, productivity, quality, and agility are enhanced while reducing the need for repetitive work and manual efforts. Implementing scalable CI/CD for development using cloud services like ECS (Container Management Service), AWS Fargate, ECR (to store Docker images with all dependencies), Serverless Computing (serverless virtual machines), Cloud Log (for monitoring errors and logs), Security Groups (for inside/outside access to the application), Docker Containerization (Docker-based images and container techniques), Jenkins (CI/CD build management tool), and code management tools (GitHub, Bitbucket, AWS CodeCommit) can efficiently handle the demands of diverse development environments and are capable of accommodating dynamic workloads, increasing efficiency for faster delivery with good quality. CI/CD pipelines encourage collaboration among development, operations, and quality assurance teams by providing a centralized platform for automated testing, deployment, and monitoring. Scalable CI/CD streamlines the development process by automatically fetching the latest code from the repository every time the process starts, building the application based on the branches, testing the application using a scalable automation testing framework, and deploying the builds. Developers can focus more on writing code and less on managing infrastructure as it scales based on the need. Serverless CI/CD eliminates the need to manage and maintain traditional CI/CD infrastructure, such as servers and build agents, reducing operational overhead and allowing teams to allocate resources more efficiently. Scalable CI/CD adjusts the application's scale according to usage, thereby alleviating concerns about scalability, maintenance costs, and resource needs. Creating scalable automation testing using cloud services (ECR, ECS Fargate, Docker, EFS, Serverless Computing) helps organizations run more than 500 test cases in parallel, aiding in the detection of race conditions, performance issues, and reducing execution time. Scalable CI/CD offers flexibility, dynamically adjusting to varying workloads and demands, allowing teams to scale resources up or down as needed. It optimizes costs by only paying for the resources as they are used and increases reliability. Scalable CI/CD pipelines employ automated testing and validation processes to detect and prevent errors early in the development cycle.

Keywords: achieve parallel execution, cloud services, scalable automation testing, scalable continuous integration and deployment

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Authors: Leonie Bradfield, Stephen Fityus, John Simmons

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The shearing behavior of current and planned coal mine spoil dumps up to 400m in height is studied using large-sample-high-stress direct shear tests performed on a range of spoils common to the coalfields of Eastern Australia. The motivation for the study is to address industry concerns that some constructed spoil dump heights ( > 350m) are exceeding the scale ( ≤ 120m) for which reliable design information exists, and because modern geotechnical laboratories are not equipped to test representative spoil specimens at field-scale stresses. For more than two decades, shear strength estimation for spoil dumps has been based on either infrequent, very small-scale tests where oversize particles are scalped to comply with device specimen size capacity such that the influence of prototype-sized particles on shear strength is not captured; or on published guidelines that provide linear shear strength envelopes derived from small-scale test data and verified in practice by slope performance of dumps up to 120m in height. To date, these published guidelines appear to have been reliable. However, in the field of rockfill dam design there is a broad acceptance of a curvilinear shear strength envelope, and if this is applicable to coal mine spoils, then these industry-accepted guidelines may overestimate the strength and stability of dumps at higher stress levels. The pressing need to rationally define the shearing behavior of more representative spoil specimens at field-scale stresses led to the successful design, construction and operation of a large direct shear machine (LDSM) and its subsequent application to provide reliable design information for current and planned very-high dumps. The LDSM can test at a much larger scale, in terms of combined specimen size (720mm x 720mm x 600mm) and stress (σn up to 4.6MPa), than has ever previously been achieved using a direct shear machine for geotechnical testing of rockfill. The results of an extensive LDSM testing program on a wide range of coal-mine spoils are compared to a published framework that widely accepted by the Australian coal mining industry as the standard for shear strength characterization of mine spoil. A critical outcome is that the LDSM data highlights several non-compliant spoils, and stress-dependent shearing behavior, for which the correct application of the published framework will not provide reliable shear strength parameters for design. Shear strength envelopes developed from the LDSM data are also compared with dam engineering knowledge, where failure envelopes of rockfills are curved in a concave-down manner. The LDSM data indicates that shear strength envelopes for coal-mine spoils abundant with rock fragments are not in fact curved and that the shape of the failure envelope is ultimately determined by the strength of rock fragments. Curvilinear failure envelopes were found to be appropriate for soil-like spoils containing minor or no rock fragments, or hard-soil aggregates.

Keywords: coal mine, direct shear test, high dump, large scale, mine spoil, shear strength, spoil dump

Procedia PDF Downloads 159

Authors: Sree Bash Chandra Debnath, Didier Tonneau, Carole Fauquet, Agnes Tallet, Julien Darreon

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Purpose: Inorganic scintillating dosimetry is the most recent promising technique to solve several dosimetric issues and provide quality assurance in radiation therapy. Despite several advantages, the major issue of using scintillating detectors is the Cerenkov effect, typically induced in the visible emission range. In this context, the purpose of this research work is to evaluate the performance of a novel infrared inorganic scintillator detector (IR-ISD) in the radiation therapy treatment to ensure Cerenkov free signal and the best matches between the delivered and prescribed doses during treatment. Methods: A simple and small-scale infrared inorganic scintillating detector of 100 µm diameter with a sensitive scintillating volume of 2x10-6 mm3 was developed. A prototype of the dose verification system has been introduced based on PTIR1470/F (provided by Phosphor Technology®) material used in the proposed novel IR-ISD. The detector was tested on an Elekta LINAC system tuned at 6 MV/15MV and a brachytherapy source (Ir-192) used in the patient treatment protocol. The associated dose rate was measured in count rate (photons/s) using a highly sensitive photon counter (sensitivity ~20ph/s). Overall measurements were performed in IBATM water tank phantoms by following international Technical Reports series recommendations (TRS 381) for radiotherapy and TG43U1 recommendations for brachytherapy. The performance of the detector was tested through several dosimetric parameters such as PDD, beam profiling, Cerenkov measurement, dose linearity, dose rate linearity repeatability, and scintillator stability. Finally, a comparative study is also shown using a reference microdiamond dosimeter, Monte-Carlo (MC) simulation, and data from recent literature. Results: This study is highlighting the complete removal of the Cerenkov effect especially for small field radiation beam characterization. The detector provides an entire linear response with the dose in the 4cGy to 800 cGy range, independently of the field size selected from 5 x 5 cm² down to 0.5 x 0.5 cm². A perfect repeatability (0.2 % variation from average) with day-to-day reproducibility (0.3% variation) was observed. Measurements demonstrated that ISD has superlinear behavior with dose rate (R2=1) varying from 50 cGy/s to 1000 cGy/s. PDD profiles obtained in water present identical behavior with a build-up maximum depth dose at 15 mm for different small fields irradiation. A low dimension of 0.5 x 0.5 cm² field profiles have been characterized, and the field cross profile presents a Gaussian-like shape. The standard deviation (1σ) of the scintillating signal remains within 0.02% while having a very low convolution effect, thanks to lower sensitive volume. Finally, during brachytherapy, a comparison with MC simulations shows that considering energy dependency, measurement agrees within 0.8% till 0.2 cm source to detector distance. Conclusion: The proposed scintillating detector in this study shows no- Cerenkov radiation and efficient performance for several radiation therapy measurement parameters. Therefore, it is anticipated that the IR-ISD system can be promoted to validate with direct clinical investigations, such as appropriate dose verification and quality control in the Treatment Planning System (TPS).

Keywords: IR-Scintillating detector, dose measurement, micro-scintillators, Cerenkov effect

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Authors: Farah Vierra

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Following the 2016 US presidential election and the advancement of the Brexit referendum, the concept of “post-truth”, defined by Oxford Dictionary as “relating to or denoting circumstances in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief”, came into prominent use in public, political and educational circles. What this essentially entails is that in this age, individuals are increasingly confronted with subjective perpetuations of truth in their discourse spheres that are informed by beliefs and opinions as opposed to any form of coherence to the reality of those who these truth claims concern. In principle, a subjective delineation of truth is progressive and liberating – especially considering its potential in providing marginalised groups in the diverse communities of our globalised world with the voice to articulate truths that are representative of themselves and their experiences. However, any form of human flourishing that seems to be promised here collapses as the tenets of subjective truths initially in place to liberate has been distorted through post-truth to allow individuals to purport selective and individualistic truth claims that further oppress and silence certain groups within society without due accountability. The evidence of which is prevalent through the conception of terms such as "alternative facts" and "fake news" that we observe individuals declare when their problematic truth claims are questioned. Considering the pervasiveness of post-truth and the ethical issues that accompany it, educators and scholars alike have increasingly noted the need to adapt educational practices and pedagogies to account for the diminishing objectivity of truth in the twenty-first century, especially because students, as digital natives, find themselves in the firing line of post-truth; engulfed in digital societies that proliferate post-truth through the surge of truth claims allowed in various media sites. In an attempt to equip students with the vital skills to navigate the post-truth age and oppose its proliferation of social injustices, English educators find themselves having to devise instructional strategies that not only teach students the ways they can critically and ethically scrutinise truth claims but also teach them to mediate the subjectivity of truth in a manner that does not undermine the voices of diverse communities. In hopes of providing educators with the roadmap to do so, this paper will first examine the challenges that confront students as a result of post-truth. Following which, the paper will elucidate the role English education can play in helping students overcome the complex ramifications of post-truth. Scholars have consistently touted the affordances of literary texts in providing students with imagined spaces to explore societal issues through a critical discernment of language and an ethical engagement with its narrative developments. Therefore, this paper will explain and demonstrate how literary texts, when used alongside a critical-ethical post-truth pedagogy that equips students with interpretive strategies informed by literary traditions such as literary and ethical criticism, can be effective in helping students develop the pertinent skills to comprehensively examine truth claims and overcome the challenges of the post-truth age.

Keywords: post-truth, pedagogy, ethics, English, education

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Authors: Pompilia Buzatu, Hazim Qiblawey, Albert Odai, Jana Jamaleddin, Mustafa Nasser, Simon J. Judd

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Membrane bioreactor (MBR) technology is challenged by the tendency for the membrane permeability to decrease due to ‘clogging’. Clogging includes ‘sludging’, the filling of the membrane channels with sludge solids, and ‘ragging’, the aggregation of short filaments to form long rag-like particles. Both sludging and ragging demand manual intervention to clear out the solids, which is time-consuming, labour-intensive and potentially damaging to the membranes. These factors impact on costs more significantly than membrane surface fouling which, unlike clogging, is largely mitigated by the chemical clean. However, practical evaluation of MBR clogging has thus far been limited. This paper presents the results of recent work attempting to quantify sludging and clogging based on simple bench-scale tests. Results from a novel ragging simulation trial indicated that rags can be formed within 24-36 hours from dispersed < 5 mm-long filaments at concentrations of 5-10 mg/L under gently agitated conditions. Rag formation occurred for both a cotton wool standard and samples taken from an operating municipal MBR, with between 15% and 75% of the added fibrous material forming a single rag. The extent of rag formation depended both on the material type or origin – lint from laundering operations forming zero rags – and the filament length. Sludging rates were quantified using a bespoke parallel-channel test cell representing the membrane channels of an immersed flat sheet MBR. Sludge samples were provided from two local MBRs, one treating municipal and the other industrial effluent. Bulk sludge properties measured comprised mixed liquor suspended solids (MLSS) concentration, capillary suction time (CST), particle size, soluble COD (sCOD) and rheology (apparent viscosity μₐ vs shear rate γ). The fouling and sludging propensity of the sludge was determined using the test cell, ‘fouling’ being quantified as the pressure incline rate against flux via the flux step test (for which clogging was absent) and sludging by photographing the channel and processing the image to determine the ratio of the clogged to unclogged regions. A substantial difference in rheological and fouling behaviour was evident between the two sludge sources, the industrial sludge having a higher viscosity but less shear-thinning than the municipal. Fouling, as manifested by the pressure increase Δp/Δt, as a function of flux from classic flux-step experiments (where no clogging was evident), was more rapid for the industrial sludge. Across all samples of both sludge origins the expected trend of increased fouling propensity with increased CST and sCOD was demonstrated, whereas no correlation was observed between clogging rate and these parameters. The relative contribution of fouling and clogging was appraised by adjusting the clogging propensity via increasing the MLSS both with and without a commensurate increase in the COD. Results indicated that whereas for the municipal sludge the fouling propensity was affected by the increased sCOD, there was no associated increased in the sludging propensity (or cake formation). The clogging rate actually decreased on increasing the MLSS. Against this, for the industrial sludge the clogging rate dramatically increased with solids concentration despite a decrease in the soluble COD. From this was surmised that sludging did not relate to fouling.

Keywords: clogging, membrane bioreactors, ragging, sludge

Procedia PDF Downloads 177

Authors: Lynn Sheridan, Dennis Alonzo, Hoa Nguyen, Andy Gao, Tracy Durksen

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Disruptions to teaching (e.g., COVID-related) have increased work demands for teachers. There is an opportunity for research to explore evidence-informed steps to support teachers. Collective evidence informs data on teachers’ personal attributes (e.g., self-efficacy beliefs) in the workplace are seen to promote success in teaching and support teacher engagement. Teacher engagement plays a role in students’ learning and teachers’ effectiveness. Engaged teachers are better at overcoming work-related stress, burnout and are more likely to take on active roles. Teachers’ commitment is influenced by a host of personal (e.g., teacher well-being) and environmental factors (e.g., job stresses). The job demands-resources model provided a conceptual basis for examining how teachers’ well-being, and is influenced by job demands and job resources. Job demands potentially evoke strain and exceed the employee’s capability to adapt. Job resources entail what the job offers to individual teachers (e.g., organisational support), helping to reduce job demands. The application of the job demands-resources model involves gathering an evidence-base of and connection to personal attributes (job resources). The study explored the association between constructs (resilience, adaptability, commitment, self/collective efficacy) and a teacher’s engagement with the job. The paper sought to elaborate on the model and determine the associations between key constructs of well-being (resilience, adaptability), commitment, and motivation (self and collective-efficacy beliefs) to teachers’ engagement in teaching. Data collection involved online a multi-dimensional instrument using validated items distributed from 2020-2022. The instrument was designed to identify construct relationships. The participant number was 170. Data Analysis: The reliability coefficients, means, standard deviations, skewness, and kurtosis statistics for the six variables were completed. All scales have good reliability coefficients (.72-.96). A confirmatory factor analysis (CFA) and structural equation model (SEM) were performed to provide measurement support and to obtain latent correlations among factors. The final analysis was performed using structural equation modelling. Several fit indices were used to evaluate the model fit, including chi-square statistics and root mean square error of approximation. The CFA and SEM analysis was performed. The correlations of constructs indicated positive correlations exist, with the highest found between teacher engagement and resilience (r=.80) and the lowest between teacher adaptability and collective teacher efficacy (r=.22). Given the associations; we proceeded with CFA. The CFA yielded adequate fit: CFA fit: X (270, 1019) = 1836.79, p < .001, RMSEA = .04, and CFI = .94, TLI = .93 and SRMR = .04. All values were within the threshold values, indicating a good model fit. Results indicate that increasing teacher self-efficacy beliefs will increase a teacher’s level of engagement; that teacher ‘adaptability and resilience are positively associated with self-efficacy beliefs, as are collective teacher efficacy beliefs. Implications for school leaders and school systems: 1. investing in increasing teachers’ sense of efficacy beliefs to manage work demands; 2. leadership approaches can enhance teachers' adaptability and resilience; and 3. a culture of collective efficacy support. Preparing teachers for now and in the future offers an important reminder to policymakers and school leaders on the importance of supporting teachers’ personal attributes when faced with the challenging demands of the job.

Keywords: collective teacher efficacy, teacher self-efficacy, job demands, teacher engagement

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Authors: Suzanne Phibbs, Christine Kenney, Robyn Richardson

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The Sendai Framework for Disaster Risk Reduction called for the inclusion of indigenous people in the design and implementation of all hazard policies, plans, and standards. Ensuring that indigenous knowledge practices were included alongside scientific knowledge about disaster risk was also a key priority. Indigenous communities have specific knowledge about climate and natural hazard risk that has been developed over an extended period of time. However, research within indigenous communities can be fraught with issues such as power imbalances between the researcher and researched, the privileging of researcher agendas over community aspirations, as well as appropriation and/or inappropriate use of indigenous knowledge. This paper documents the process of working alongside a Māori community to develop a successful community-led research project. Research Design: This case study documents the development of a qualitative community-led participatory project. The community research project utilizes a kaupapa Māori research methodology which draws upon Māori research principles and concepts in order to generate knowledge about Māori resilience. The research addresses a significant gap in the disaster research literature relating to indigenous knowledge about collective hazard mitigation practices as well as resilience in rurally isolated indigenous communities. The research was designed in partnership with the Ngāti Raukawa Northern Marae Collective as well as Ngā Wairiki Ngāti Apa (a group of Māori sub-tribes who are located in the same region) and will be conducted by Māori researchers utilizing Māori values and cultural practices. The research project aims and objectives, for example, are based on themes that were identified as important to the Māori community research partners. The research methodology and methods were also negotiated with and approved by the community. Kaumātua (Māori elders) provided cultural and ethical guidance over the proposed research process and will continue to provide oversight over the conduct of the research. Purposive participant recruitment will be facilitated with support from local Māori community research partners, utilizing collective marae networks and snowballing methods. It is envisaged that Māori participants’ knowledge, experiences and views will be explored using face-to-face communication research methods such as workshops, focus groups and/or semi-structured interviews. Interviews or focus groups may be held in English and/or Te Reo (Māori language) to enhance knowledge capture. Analysis, knowledge dissemination, and co-authorship of publications will be negotiated with the Māori community research partners. Māori knowledge shared during the research will constitute participants’ intellectual property. New knowledge, theory, frameworks, and practices developed by the research will be co-owned by Māori, the researchers, and the host academic institution. Conclusion: An emphasis on indigenous knowledge systems within the Sendai Framework for Disaster Risk Reduction risks the appropriation and misuse of indigenous experiences of disaster risk identification, mitigation, and response. The research protocol underpinning this project provides an exemplar of collaborative partnership in the development and implementation of an indigenous project that has relevance to policymakers, academic researchers, other regions with indigenous communities and/or local disaster risk reduction knowledge practices.

Keywords: community resilience, indigenous disaster risk reduction, Maori, research methods

Procedia PDF Downloads 124

Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Priscila Ribeiro dos Santos, Luiz Antonio Daniel

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Inadequate access to clean water and sanitation has become one of the most widespread problems affecting people throughout the developing world, leading to an unceasing need for low-cost and sustainable wastewater treatment systems. The UASB technology has been widely employed as a suitable and economical option for the treatment of sewage in developing countries, which involves low initial investment, low energy requirements, low operation and maintenance costs, high loading capacity, short hydraulic retention times, long solids retention times and low sludge production. Whereas dissolved air flotation process is a good option for the post-treatment of anaerobic effluents, being capable of producing high quality effluents in terms of total suspended solids, chemical oxygen demand, phosphorus, and even pathogens. This work presents an evaluation and monitoring, over a period of 6 months, of one compact full-scale system with this configuration, UASB reactors followed by dissolved air flotation units (DAF), operating in Brazil. It was verified as a successful treatment system, and an issue of relevance since dissolved air flotation process treating UASB reactor effluents is not widely encompassed in the literature. The study covered the removal and behavior of several variables, such as turbidity, total suspend solids (TSS), chemical oxygen demand (COD), Escherichia coli, total coliforms and Clostridium perfringens. The physicochemical variables were analyzed according to the protocols established by the Standard Methods for Examination of Water and Wastewater. For microbiological variables, such as Escherichia coli and total coliforms, it was used the “pour plate” technique with Chromocult Coliform Agar (Merk Cat. No.1.10426) serving as the culture medium, while the microorganism Clostridium perfringens was analyzed through the filtering membrane technique, with the Ágar m-CP (Oxoid Ltda, England) serving as the culture medium. Approximately 74% of total COD was removed in the UASB reactor, and the complementary removal done during the flotation process resulted in 88% of COD removal from the raw sewage, thus the initial concentration of COD of 729 mg.L-1 decreased to 87 mg.L-1. Whereas, in terms of particulate COD, the overall removal efficiency for the whole system was about 94%, decreasing from 375 mg.L-1 in raw sewage to 29 mg.L-1 in final effluent. The UASB reactor removed on average 77% of the TSS from raw sewage. While the dissolved air flotation process did not work as expected, removing only 30% of TSS from the anaerobic effluent. The final effluent presented an average concentration of 38 mg.L-1 of TSS. The turbidity was significantly reduced, leading to an overall efficiency removal of 80% and a final turbidity of 28 NTU.The treated effluent still presented a high concentration of fecal pollution indicators (E. coli, total coliforms, and Clostridium perfringens), showing that the system did not present a good performance in removing pathogens. Clostridium perfringens was the organism which suffered the higher removal by the treatment system. The results can be considered satisfactory for the physicochemical variables, taking into account the simplicity of the system, besides that, it is necessary a post-treatment to improve the microbiological quality of the final effluent.

Keywords: dissolved air flotation, municipal sewage, UASB reactor, treatment

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Authors: Zihan Geng, L. Quentin Dixon

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It has been proposed that early bilingual experience confers a number of advantages in the development of executive control mechanisms. Although the literature provides empirical evidence for bilingual benefits, some studies also reported null or mixed results. To make sense of these contradictory findings, the current review synthesize recent empirical studies investigating bilingual effects on children’s executive function and attention control. The publication time of the studies included in the review ranges from 2010 to 2017. The key searching terms are bilingual, bilingualism, children, executive control, executive function, and attention. The key terms were combined within each of the following databases: ERIC (EBSCO), Education Source, PsycINFO, and Social Science Citation Index. Studies involving both children and adults were also included but the analysis was based on the data generated only by the children group. The initial search yielded 137 distinct articles. Twenty-eight studies from 27 articles with a total of 3367 participants were finally included based on the selection criteria. The selective studies were then coded in terms of (a) the setting (i.e., the country where the data was collected), (b) the participants (i.e., age and languages), (c) sample size (i.e., the number of children in each group), (d) cognitive outcomes measured, (e) data collection instruments (i.e., cognitive tasks and tests), and (f) statistic analysis models (e.g., t-test, ANOVA). The results show that the majority of the studies were undertaken in western countries, mainly in the U.S., Canada, and the UK. A variety of languages such as Arabic, French, Dutch, Welsh, German, Spanish, Korean, and Cantonese were involved. In relation to cognitive outcomes, the studies examined children’s overall planning and problem-solving abilities, inhibition, cognitive complexity, working memory (WM), and sustained and selective attention. The results indicate that though bilingualism is associated with several cognitive benefits, the advantages seem to be weak, at least, for children. Additionally, the nature of the cognitive measures was found to greatly moderate the results. No significant differences are observed between bilinguals and monolinguals in overall planning and problem-solving ability, indicating that there is no bilingual benefit in the cooperation of executive function components at an early age. In terms of inhibition, the mixed results suggest that bilingual children, especially young children, may have better conceptual inhibition measured in conflict tasks, but not better response inhibition measured by delay tasks. Further, bilingual children showed better inhibitory control to bivalent displays, which resembles the process of maintaining two language systems. The null results were obtained for both cognitive complexity and WM, suggesting no bilingual advantage in these two cognitive components. Finally, findings on children’s attention system associate bilingualism with heightened attention control. Together, these findings support the hypothesis of cognitive benefits for bilingual children. Nevertheless, whether these advantages are observable appears to highly depend on the cognitive assessments. Therefore, future research should be more specific about the cognitive outcomes (e.g., the type of inhibition) and should report the validity of the cognitive measures consistently.

Keywords: attention, bilingual advantage, children, executive function

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Authors: Lewis J. Woollin, Robert I. Davidson, Paul Watson, Philip J. Hyde

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Introduction: In-vitro testing of arthroplasty materials is of paramount importance when ensuring that they can withstand the performance requirements encountered in-vivo. One common machine used for in-vitro testing is a pin-on-plate tribometer, an early stage screening device that generates data on the wear characteristics of arthroplasty bearing materials. These devices test vertically loaded rotating cylindrical pins acting against reciprocating plates, representing the bearing surfaces. In this study, a pin-on-plate machine has been developed that provides several improvements over current technology, thereby progressing arthroplasty bearing research. Historically, pin-on-plate tribometers have been used to investigate the performance of arthroplasty bearing materials under conditions commonly encountered during a standard gait cycle; nominal operating pressures of 2-6 MPa and an operating frequency of 1 Hz are typical. There has been increased interest in using pin-on-plate machines to test more representative in-vivo conditions, due to the drive to test 'beyond compliance', as well as their testing speed and economic advantages over hip simulators. Current pin-on-plate machines do not accommodate the increased performance requirements associated with more extreme kinematic conditions, therefore a next-generation pin-on-plate tribometer has been developed to bridge the gap between current technology and future research requirements. Methodology: The design was driven by several physiologically relevant requirements. Firstly, an increased loading capacity was essential to replicate the peak pressures that occur in the natural hip joint during running and chair-rising, as well as increasing the understanding of wear rates in obese patients. Secondly, the introduction of mid-cycle load variation was of paramount importance, as this allows for an approximation of the loads present in a gait cycle to be applied and to test the fatigue properties of materials. Finally, the rig must be validated against previous-generation pin-on-plate and arthroplasty wear data. Results: The resulting machine is a twelve station device that is split into three sets of four stations, providing an increased testing capacity compared to most current pin-on-plate tribometers. The loading of the pins is generated using a pneumatic system, which can produce contact pressures of up to 201 MPa on a 3.2 mm² round pin face. This greatly exceeds currently achievable contact pressures in literature and opens new research avenues such as testing rim wear of mal-positioned hip implants. Additionally, the contact pressure of each set can be changed independently of the others, allowing multiple loading conditions to be tested simultaneously. Using pneumatics also allows the applied pressure to be switched ON/OFF mid-cycle, another feature not currently reported elsewhere, which allows for investigation into intermittent loading and material fatigue. The device is currently undergoing a series of validation tests using Ultra-High-Molecular-Weight-Polyethylene pins and 316L Stainless Steel Plates (polished to a Ra < 0.05 µm). The operating pressures will be between 2-6 MPa, operating at 1 Hz, allowing for validation of the machine against results reported previously in the literature. The successful production of this next-generation pin-on-plate tribometer will, following its validation, unlock multiple previously unavailable research avenues.

Keywords: arthroplasty, mechanical design, pin-on-plate, total joint replacement, wear testing

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Thilini M. Yatanwala

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CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

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Authors: Nikolaus Wilke, Boaz Paz

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Museum staff, conservators, restorers, curators, registrars, art handlers but potentially also museum visitors are often exposed to the harmful effects of biocides, which have been applied to collections in the past for the protection and preservation of cultural heritage. Due to stable light, moisture, and temperature conditions, the biocidal active ingredients were preserved for much longer than originally assumed by chemists, pest controllers, and museum scientists. Given the requirements to minimize the use and handling of toxic substances and the obligations of employers regarding safe working environments for their employees, but also for visitors, the museum sector worldwide needs adequate decontamination solutions. Today there are millions of contaminated objects in museums. This paper introduces the results of a systematic investigation into the reduction rate of biocide contamination in various organic materials that were treated with the humidity and temperature controlled ICM (Integrated Contamination Management) method. In the past, collections were treated with a wide range, at times even with a combination of toxins, either preventively or to eliminate active insect or fungi infestations. It was only later that most of those toxins were recognized as CMR (cancerogenic mutagen reprotoxic) substances. Among them were numerous chemical substances that are banned today because of their toxicity. While the biocidal effect of inorganic salts such as arsenic (arsenic(III) oxide), sublimate (mercury(II) chloride), copper oxychloride (basic copper chloride) and zinc chloride was known very early on, organic tar distillates such as paradichlorobenzene, carbolineum, creosote and naphthalene were increasingly used from the 19th century onwards, especially as wood preservatives. With the rapid development of organic synthesis chemistry in the 20th century and the development of highly effective warfare agents, pesticides and fungicides, these substances were replaced by chlorogenic compounds (e.g. γ-hexachlorocyclohexane (lindane), dichlorodiphenyltrichloroethane (DDT), pentachlorophenol (PCP), hormone-like derivatives such as synthetic pyrethroids (e.g., permethrin, deltamethrin, cyfluthrin) and phosphoric acid esters (e.g., dichlorvos, chlorpyrifos). Today we know that textile artifacts (costumes, uniforms, carpets, tapestries), wooden objects, herbaria, libraries, archives and historical wall decorations made of fabric, paper and leather were also widely treated with toxic inorganic and organic substances. The migration (emission) of pollutants from the contaminated objects leads to continuous (secondary) contamination and accumulation in the indoor air and dust. It is important to note that many of mentioned toxic substances are also material-damaging; they cause discoloration and corrosion. Some, such as DDT, form crystals, which in turn can cause micro tectonic, destructive shifting, for example, in paint layers. Museums must integrate sustainable solutions to address the residual biocide problems already in the planning phase. Gas and dust phase measurements and analysis must become standard as well as methods of decontamination.

Keywords: biocides, decontamination, museum collections, toxic substances in museums

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Authors: Amarendar Reddy Addula

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Definition of Artificial Intelligence: Artificial intelligence is the simulation of mortal intelligence processes by machines, especially computer systems. Explicit operations of AI comprise expert systems, natural language processing, and speech recognition, and machine vision. Artificial Intelligence (AI) is an original medium for digital business, according to a new report by Gartner. The last 10 times represent an advance period in AI’s development, prodded by the confluence of factors, including the rise of big data, advancements in cipher structure, new machine literacy ways, the materialization of pall computing, and the vibrant open- source ecosystem. Influence of AI to a broader set of use cases and druggies and its gaining fashionability because it improves AI’s versatility, effectiveness, and rigidity. Edge AI will enable digital moments by employing AI for real- time analytics closer to data sources. Gartner predicts that by 2025, further than 50 of all data analysis by deep neural networks will do at the edge, over from lower than 10 in 2021. Responsible AI is a marquee term for making suitable business and ethical choices when espousing AI. It requires considering business and societal value, threat, trust, translucency, fairness, bias mitigation, explainability, responsibility, safety, sequestration, and nonsupervisory compliance. Responsible AI is ever more significant amidst growing nonsupervisory oversight, consumer prospects, and rising sustainability pretensions. Generative AI is the use of AI to induce new vestiges and produce innovative products. To date, generative AI sweats have concentrated on creating media content similar as photorealistic images of people and effects, but it can also be used for law generation, creating synthetic irregular data, and designing medicinals and accoutrements with specific parcels. AI is the subject of a wide- ranging debate in which there's a growing concern about its ethical and legal aspects. Constantly, the two are varied and nonplussed despite being different issues and areas of knowledge. The ethical debate raises two main problems the first, abstract, relates to the idea and content of ethics; the alternate, functional, and concerns its relationship with the law. Both set up models of social geste, but they're different in compass and nature. The juridical analysis is grounded on anon-formalistic scientific methodology. This means that it's essential to consider the nature and characteristics of the AI as a primary step to the description of its legal paradigm. In this regard, there are two main issues the relationship between artificial and mortal intelligence and the question of the unitary or different nature of the AI. From that theoretical and practical base, the study of the legal system is carried out by examining its foundations, the governance model, and the nonsupervisory bases. According to this analysis, throughout the work and in the conclusions, International Law is linked as the top legal frame for the regulation of AI.

Keywords: artificial intelligence, ethics & human rights issues, laws, international laws

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