Search results for: financial algorithm

Authors: David Bakker, Nikki Rickard

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Smartphone apps hold immense potential as mental health and wellbeing tools. Support can be made easily accessible and can be used in real-time while users are experiencing distress. Furthermore, data can be collected to enable machine learning and automated tailoring of support to users. While many apps have been developed for mental health purposes, few have adhered to evidence-based recommendations and even fewer have pursued experimental validation. This paper details the development and experimental evaluation of an app, MoodMission, that aims to provide support for low moods and anxiety, help prevent clinical depression and anxiety disorders, and serve as an adjunct to professional clinical supports. MoodMission was designed to deliver cognitive behavioural therapy for specifically reported problems in real-time, momentary interactions. Users report their low moods or anxious feelings to the app along with a subjective units of distress scale (SUDS) rating. MoodMission then provides a choice of 5-10 short, evidence-based mental health strategies called Missions. Users choose a Mission, complete it, and report their distress again. Automated tailoring, gamification, and in-built data collection for analysis of effectiveness was also included in the app’s design. The development process involved construction of an evidence-based behavioural plan, designing of the app, building and testing procedures, feedback-informed changes, and a public launch. A randomized controlled trial (RCT) was conducted comparing MoodMission to two other apps and a waitlist control condition. Participants completed measures of anxiety, depression, well-being, emotional self-awareness, coping self-efficacy and mental health literacy at the start of their app use and 30 days later. At the time of submission (November 2016) over 300 participants have participated in the RCT. Data analysis will begin in January 2017. At the time of this submission, MoodMission has over 4000 users. A repeated-measures ANOVA of 1390 completed Missions reveals that SUDS (0-10) ratings were significantly reduced between pre-Mission ratings (M=6.20, SD=2.39) and post-Mission ratings (M=4.93, SD=2.25), F(1,1389)=585.86, p < .001, np2=.30. This effect was consistent across both low moods and anxiety. Preliminary analyses of the data from the outcome measures surveys reveal improvements across mental health and wellbeing measures as a result of using the app over 30 days. This includes a significant increase in coping self-efficacy, F(1,22)=5.91, p=.024, np2=.21. Complete results from the RCT in which MoodMission was evaluated will be presented. Results will also be presented from the continuous outcome data being recorded by MoodMission. MoodMission was successfully developed and launched, and preliminary analysis suggest that it is an effective mental health and wellbeing tool. In addition to the clinical applications of MoodMission, the app holds promise as a research tool to conduct component analysis of psychological therapies and overcome restraints of laboratory based studies. The support provided by the app is discrete, tailored, evidence-based, and transcends barriers of stigma, geographic isolation, financial limitations, and low health literacy.

Keywords: anxiety, app, CBT, cognitive behavioural therapy, depression, eHealth, mission, mobile, mood, MoodMission

Procedia PDF Downloads 259

Authors: Alon Cohen, Jeffrey Kantor, Shalom Levy

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The use of the audit risk model in auditing has faced limitations and difficulties, leading auditors to rely on a conceptual level of its application. The qualitative approach to assessing risks has resulted in different risk assessments, affecting the quality of audits and decision-making on the adoption of CAATTs. This study aims to investigate risk factors impacting the implementation of the audit risk model and propose a complementary risk-based instrument (KRIs) to form substance risk judgments and mitigate against heightened risk of material misstatement (RMM). The study addresses the question of how risk factors impact the implementation of the audit risk model, improve risk judgments, and aid in the adoption of CAATTs. The study uses a three-stage scale development procedure involving a pretest and subsequent study with two independent samples. The pretest involves an exploratory factor analysis, while the subsequent study employs confirmatory factor analysis for construct validation. Additionally, the authors test the ability of the KRIs to predict audit efforts needed to mitigate against heightened RMM. Data was collected through two independent samples involving 767 participants. The collected data was analyzed using exploratory factor analysis and confirmatory factor analysis to assess scale validity and construct validation. The suggested KRIs, comprising two risk components and seventeen risk items, are found to have high predictive power in determining audit efforts needed to reduce RMM. The study validates the suggested KRIs as an effective instrument for risk assessment and decision-making on the adoption of CAATTs. This study contributes to the existing literature by implementing a holistic approach to risk assessment and providing a quantitative expression of assessed risks. It bridges the gap between intuitive risk evaluation and the theoretical domain, clarifying the mechanism of risk assessments. It also helps improve the uniformity and quality of risk assessments, aiding audit standard-setters in issuing updated guidelines on CAATT adoption. A few limitations and recommendations for future research should be mentioned. First, the process of developing the scale was conducted in the Israeli auditing market, which follows the International Standards on Auditing (ISAs). Although ISAs are adopted in European countries, for greater generalization, future studies could focus on other countries that adopt additional or local auditing standards. Second, this study revealed risk factors that have a material impact on the assessed risk. However, there could be additional risk factors that influence the assessment of the RMM. Therefore, future research could investigate other risk segments, such as operational and financial risks, to bring a broader generalizability to our results. Third, although the sample size in this study fits acceptable scale development procedures and enables drawing conclusions from the body of research, future research may develop standardized measures based on larger samples to reduce the generation of equivocal results and suggest an extended risk model.

Keywords: audit risk model, audit efforts, CAATTs adoption, key risk indicators, sustainability

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Authors: Soma Kanta Baral

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Background: Since 1981, when the first AIDS case was reported, worldwide, more than 34 million people have been infected with HIV. Almost 95 percent of the people infected with HIV live in developing countries. As HBV & HIV share similar routes of transmission by sexual intercourse or drug use by parenteral injection, co-infection is common. Because of the limited access to healthcare & HIV treatment in developing countries, HIV-infected individuals are present late for care. Enumeration of CD4+ T cell count at the time of diagnosis has been useful to initiate the therapy in HIV infected individuals. The baseline CD4+ T cell count shows high immunological variability among patients. Methods: This prospective study was done in the serology section of the Department of Microbiology over a period of one year from august 2012 to July 2013. A total of 13037 individuals subjected for HIV test were included in the study comprising of 4982 males & 8055 females. Blood sample was collected by vein puncture aseptically with standard operational procedure in clean & dry test-tube. All blood samples were screened for HIV as described by WHO algorithm by Immuno-chromatography rapid kits. Further confirmation was done by biokit ELISA method as per the manufacturer’s guidelines. After informed consent, HIV positive individuals were screened for HBsAg by Immuno-chromatography rapid kits (Hepacard). Further confirmation was done by biokit ELISA method as per the manufacturer’s guidelines. EDTA blood samples were collected from the HIV sero-positive individuals for baseline CD4+ T count. Then, CD4+ T cells count was determined by using FACS Calibur Flow Cytometer (BD). Results: Among 13037 individuals screened for HIV, 104 (0.8%) were found to be infected comprising of 69(66.34%) males & 35 (33.65%) females. The study showed that the high infection was noted in housewives (28.7%), active age group (30.76%), rural area (56.7%) & in heterosexual route (80.9%) of transmission. Out of total HIV infected individuals, distribution of HBV co-infection was found to be 6(5.7%). All co- infected individuals were married, male, above the age of 25 years & heterosexual route of transmission. Baseline CD4+ T cell count of HIV infected patient was found higher (mean CD4+ T cell count; 283cells/cu.mm) than HBV co-infected patients (mean CD4+ T cell count; 91 cells/cu.mm). Majority (77.2%) of HIV infected & all co-infected individuals were presented in our center late (CD4+ T cell count;< 350/cu. mm) for diagnosis and care. Majority of co- infected 4 (80%) were late presented with advanced AIDS stage (CD4+ count; <200/cu.mm). Conclusions: The study showed a high percentage of HIV sero-positive & co- infected individuals. Baseline CD4+ T cell count of majority of HIV infected individuals was found to be low. Hence, more sustained and vigorous awareness campaigns & counseling still need to be done in order to promote early diagnosis and management.

Keywords: HIV/AIDS, HBsAg, co-infection, CD4+

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Authors: Vasundhara H. Krishnani, Ajay Saini, Dibesh Karmacharya, Salit Kark

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Illegal Wildlife Trade is one of the most pressing global conservation challenges. Unregulated wildlife trade can threaten biodiversity, contribute to habitat loss, limit sustainable development efforts, and expedite species declines and extinctions. In low-income and middle-income countries, such as Nepal and other countries in Asia and Africa, many of the people engaged in the early stages of illegal wildlife trade, which includes the hunting and transportation of wildlife, belong to Indigenous tribes and local communities.These countries primarily rely on punitive measures to prevent and suppress Illegal Wildlife Trade. For example, in Nepal, people involved in wildlife crimes can often be sentenced to incarceration and a hefty fine and serve up to 15 years in prison. Despite these harsh punitive measures, illegal wildlife trade remains a significant conservation challenge in many countries. The aim of this study was to examine factors affecting the participation of Indigenous communities in Illegal Wildlife Trade while recording the experiences of members of the Indigenous Chepang community, some of whom were imprisoned for their alleged involvement in rhino poaching. Chepangs, belonging to traditionally a hunter-gatherer community, are often considered an isolated and marginalized Indigenous community, some of whom live around the Chitwan National Park in Nepal. Established in 1973, Chitwan National Park is situated in the Chitwan Valley of Nepal and was one of the first regions that was declared as a protected area in Nepal, aiming to protect the one-horned rhinoceros as a flagship species. Conducted over a period of three years, this study used semi-structured interviews and focus group discussions to collect data from Illegal Wildlife Trade offenders, family members of offenders, community Elders, NGO personnel, community forest representatives, Chepang community representatives, and Government school teachers from the region surrounding Chitwan National Park. The study also examined the social, cultural, health, and financial impacts that the imprisonment of offenders had on the families of the community members, especially women and children. The results suggest that involvement of the members of the Chepang community living around Chitwan National Park in the poaching of the one-horned rhinoceros (Rhinoceros unicornis) can be attributed to a range of factors, some of which include: lack of livelihood opportunities, lack of awareness regarding wildlife rules and regulations and poverty.This work emphasises the need for raising awareness and building programs to enhance alternative livelihood training and empower indigenous and marginalised communities that provide sustainable alternatives. Furthermore, the issue needs to be addressed as a community solution which includes all community members. We suggest this multi-pronged approach can benefit wildlife conservation by reducing illegal poaching and wildlife trade, as well as community conservation in regions with similar challenges. By actively involving and empowering local communities, the communities become key stakeholders in the conservation process. This involvement contributes to protecting wildlife and natural ecosystems while simultaneously providing sustainable livelihood options for local communities.

Keywords: alternative livelihoods, chepang community, illegal wildlife trade, low-and middle-income countries, nepal, one-horned rhinoceros

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Authors: Yan Torres, Fernanda Simoes, Francisco Petrucci-Fonseca, Freddie-Jeanne Richard

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The non-invasive samples are an alternative of collecting genetic samples directly. Non-invasive samples are collected without the manipulation of the animal (e.g., scats, feathers and hairs). Nevertheless, the use of non-invasive samples has some limitations. The main issue is degraded DNA, leading to poorer extraction efficiency and genotyping. Those errors delayed for some years a widespread use of non-invasive genetic information. Possibilities to limit genotyping errors can be done using analysis methods that can assimilate the errors and singularities of non-invasive samples. Genotype matching and population estimation algorithms can be highlighted as important analysis tools that have been adapted to deal with those errors. Although, this recent development of analysis methods there is still a lack of empirical performance comparison of them. A comparison of methods with dataset different in size and structure can be useful for future studies since non-invasive samples are a powerful tool for getting information specially for endangered and rare populations. To compare the analysis methods, four different datasets used were obtained from the Dryad digital repository were used. Three different matching algorithms (Cervus, Colony and Error Tolerant Likelihood Matching - ETLM) are used for matching genotypes and two different ones for population estimation (Capwire and BayesN). The three matching algorithms showed different patterns of results. The ETLM produced less number of unique individuals and recaptures. A similarity in the matched genotypes between Colony and Cervus was observed. That is not a surprise since the similarity between those methods on the likelihood pairwise and clustering algorithms. The matching of ETLM showed almost no similarity with the genotypes that were matched with the other methods. The different cluster algorithm system and error model of ETLM seems to lead to a more criterious selection, although the processing time and interface friendly of ETLM were the worst between the compared methods. The population estimators performed differently regarding the datasets. There was a consensus between the different estimators only for the one dataset. The BayesN showed higher and lower estimations when compared with Capwire. The BayesN does not consider the total number of recaptures like Capwire only the recapture events. So, this makes the estimator sensitive to data heterogeneity. Heterogeneity in the sense means different capture rates between individuals. In those examples, the tolerance for homogeneity seems to be crucial for BayesN work properly. Both methods are user-friendly and have reasonable processing time. An amplified analysis with simulated genotype data can clarify the sensibility of the algorithms. The present comparison of the matching methods indicates that Colony seems to be more appropriated for general use considering a time/interface/robustness balance. The heterogeneity of the recaptures affected strongly the BayesN estimations, leading to over and underestimations population numbers. Capwire is then advisable to general use since it performs better in a wide range of situations.

Keywords: algorithms, genetics, matching, population

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Authors: Camelia Vizireanu, Daniela Istrati, Alina Georgiana Profir, Rodica Mihaela Dinica

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Globally, there is a great interest in promoting the consumption of fruit and vegetables to improve health. Due to the content of essential compounds such as antioxidants, important amounts of fruits and vegetables should be included in the daily diet. Juices are good sources of vitamins and can also help increase overall fruit and vegetable consumption. Starting from this trend (introduction into the daily diet of vegetables and fruits) as well as the desire to diversify the range of functional products for both adults and children, a fermented juice was made using probiotic microorganisms based on root vegetables, with potential beneficial effects in the diet of children, vegetarians and people with lactose intolerance. The three vegetables selected for this study, red beet, carrot, and celery bring a significant contribution to functional compounds such as carotenoids, flavonoids, betalain, vitamin B and C, minerals and fiber. By fermentation, the functional value of the vegetable juice increases due to the improved stability of these compounds. The combination of probiotic microorganisms and vegetable fibers resulted in a nutrient-rich synbiotic product. The stability of the nutritional and sensory qualities of the obtained synbiotic product has been tested throughout its shelf life. The evaluation of the physico-chemical changes of the synbiotic drink during storage confirmed that: (i) vegetable juice enriched with honey and vegetable pulp is an important source of nutritional compounds, especially carbohydrates and fiber; (ii) microwave treatment used to inhibit pathogenic microflora did not significantly affect nutritional compounds in vegetable juice, vitamin C concentration remained at baseline and beta-carotene concentration increased due to increased bioavailability; (iii) fermentation has improved the nutritional quality of vegetable juice by increasing the content of B vitamins, polyphenols and flavonoids and has a good antioxidant capacity throughout the shelf life; (iv) the FTIR and Raman spectra have highlighted the results obtained using physicochemical methods. Based on the analysis of IR absorption frequencies, the most striking bands belong to the frequencies 3330 cm⁻¹, 1636 cm⁻¹ and 1050 cm⁻¹, specific for groups of compounds such as polyphenols, carbohydrates, fatty acids, and proteins. Statistical data processing revealed a good correlation between the content of flavonoids, betalain, β-carotene, ascorbic acid and polyphenols, the fermented juice having a stable antioxidant activity. Also, principal components analysis showed that there was a negative correlation between the evolution of the concentration of B vitamins and antioxidant activity. Acknowledgment: This study has been founded by the Francophone University Agency, Project Réseau régional dans le domaine de la santé, la nutrition et la sécurité alimentaire (SaIN), No. at Dunarea de Jos University of Galati 21899/ 06.09.2017 and by the Sectorial Operational Programme Human Resources Development of the Romanian Ministry of Education, Research, Youth and Sports trough the Financial Agreement POSDRU/159/1.5/S/132397 ExcelDOC.

Keywords: bioactive compounds, fermentation, synbiotic drink from vegetables, stability during storage

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Authors: Kseniya Gladun

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Tactile stimulation of a dorsal side of the wrist can have a strong impact on our attitude toward physical objects such as pleasant and unpleasant impact. This study explored different aspects of tactile perception to investigate atypical touch sensitivity in children with autism spectrum disorder (ASD). This study included 40 children with ASD and 40 healthy children aged 5 to 9 years. We recorded rsEEG (sampling rate of 250 Hz) during 20 min using EEG amplifier “Encephalan” (Medicom MTD, Taganrog, Russian Federation) with 19 AgCl electrodes placed according to the International 10–20 System. The electrodes placed on the left, and right mastoids served as joint references under unipolar montage. The registration of EEG v19 assignments was carried out: frontal (Fp1-Fp2; F3-F4), temporal anterior (T3-T4), temporal posterior (T5-T6), parietal (P3-P4), occipital (O1-O2). Subjects were passively touched by 4 types of tactile stimuli on the left wrist. Our stimuli were presented with a velocity of about 3–5 cm per sec. The stimuli materials and procedure were chosen for being the most "pleasant," "rough," "prickly" and "recognizable". Type of tactile stimulation: Soft cosmetic brush - "pleasant" , Rough shoe brush - "rough", Wartenberg pin wheel roller - "prickly", and the cognitive tactile stimulation included letters by finger (most of the patient’s name ) "recognizable". To designate the moments of the stimuli onset-offset, we marked the moment when the moment of the touch began and ended; the stimulation was manual, and synchronization was not precise enough for event-related measures. EEG epochs were cleaned from eye movements by ICA-based algorithm in EEGLAB plugin for MatLab 7.11.0 (Mathwork Inc.). Muscle artifacts were cut out by manual data inspection. The response to tactile stimuli was significantly different in the group of children with ASD and healthy children, which was also depended on type of tactile stimuli and the severity of ASD. Amplitude of Alpha rhythm increased in parietal region to response for only pleasant stimulus, for another type of stimulus ("rough," "thorny", "recognizable") distinction of amplitude was not observed. Correlation dimension D2 was higher in healthy children compared to children with ASD (main effect ANOVA). In ASD group D2 was lower for pleasant and unpleasant compared to the background in the right parietal area. Hilbert transform changes in the frequency of the theta rhythm found only for a rough tactile stimulation compared with healthy participants only in the right parietal area. Children with autism spectrum disorders and healthy children were responded to tactile stimulation differently with specific frequency distribution alpha and theta band in the right parietal area. Thus, our data supports the hypothesis that rsEEG may serve as a sensitive index of altered neural activity caused by ASD. Children with autism have difficulty in distinguishing the emotional stimuli ("pleasant," "rough," "prickly" and "recognizable").

Keywords: autism, tactile stimulation, Hilbert transform, pediatric electroencephalography

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Authors: Sonja Giese, Tess N. Peacock

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South African based Innovation Edge is experimenting with technology to drive positive behavior change, enable data-driven decision making, and scale quality early years services. This paper uses five case studies to illustrate how technology can be used in resource-constrained environments to first, encourage parenting practices that build early language development (using a stage-based mobile messaging pilot, ChildConnect), secondly, to improve the quality of ECD programs (using a mobile application, CareUp), thirdly, how to affordably scale services for the early detection of visual and hearing impairments (using a mobile tool, HearX), fourthly, how to build a transparent and accountable system for the registration and funding of ECD (using a blockchain enabled platform, Amply), and finally enable rapid data collection and feedback to facilitate quality enhancement of programs at scale (the Early Learning Outcomes Measure). ChildConnect and CareUp were both developed using a design based iterative research approach. The usage and uptake of ChildConnect and CareUp was evaluated with qualitative and quantitative methods. Actual child outcomes were not measured in the initial pilots. Although parents who used and engaged on either platform felt more supported and informed, parent engagement and usage remains a challenge. This is contrast to ECD practitioners whose usage and knowledge with CareUp showed both sustained engagement and knowledge improvement. HearX is an easy-to-use tool to identify hearing loss and visual impairment. The tool was tested with 10000 children in an informal settlement. The feasibility of cost-effectively decentralising screening services was demonstrated. Practical and financial barriers remain with respect to parental consent and for successful referrals. Amply uses mobile and blockchain technology to increase impact and accountability of public services. In the pilot project, Amply is being used to replace an existing paper-based system to register children for a government-funded pre-school subsidy in South Africa. Early Learning Outcomes Measure defines what it means for a child to be developmentally ‘on track’ at aged 50-69 months. ELOM administration is enabled via a tablet which allows for easy and accurate data collection, transfer, analysis, and feedback. ELOM is being used extensively to drive quality enhancement of ECD programs across multiple modalities. The nature of ECD services in South Africa is that they are in large part provided by disconnected private individuals or Non-Governmental Organizations (in contrast to basic education which is publicly provided by the government). It is a disparate sector which means that scaling successful interventions is that much harder. All five interventions show the potential of technology to support and enhance a range of ECD services, but pathways to scale are still being tested.

Keywords: assessment, behavior change, communication, data, disabilities, mobile, scale, technology, quality

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Authors: Paula I. Buonfiglio, Carlos David Bruque, Lucia Salatino, Vanesa Lotersztein, Sebastián Menazzi, Paola Plazas, Ana Belén Elgoyhen, Viviana Dalamón

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Hearing loss (HL) is the most prevalent sensorineural disorder affecting about 10% of the global population, with more than half due to genetic causes. About 1 in 500-1000 newborns present congenital HL. Most of the patients are non-syndromic with an autosomal recessive mode of inheritance. To date, more than 100 genes are related to HL. Therefore, the Whole-exome sequencing (WES) technique has become a cost-effective alternative approach for molecular diagnosis. Nevertheless, new challenges arise from the detection of novel variants, in particular missense changes, which can lead to a spectrum of genotype-to-phenotype correlations, which is not always straightforward. In this work, we aimed to identify the genetic causes of HL in isolated and familial cases by designing a multistep approach to analyze target genes related to hearing impairment. Moreover, we performed in silico and in vivo analyses in order to further study the effect of some of the novel variants identified in the hair cell function using the zebrafish model. A total of 650 patients were studied by Sanger Sequencing and Gap-PCR in GJB2 and GJB6 genes, respectively, diagnosing 15.5% of sporadic cases and 36% of familial ones. Overall, 50 different sequence variants were detected. Fifty of the undiagnosed patients with moderate HL were tested for deletions in STRC gene by Multiplex ligation-dependent probe amplification technique (MLPA), leading to 6% of diagnosis. After this initial screening, 50 families were selected to be analyzed by WES, achieving diagnosis in 44% of them. Half of the identified variants were novel. A missense variant in MYO6 gene detected in a family with postlingual HL was selected to be further analyzed. A protein modeling with AlphaFold2 software was performed, proving its pathogenic effect. In order to functionally validate this novel variant, a knockdown phenotype rescue assay in zebrafish was carried out. Injection of wild-type MYO6 mRNA in embryos rescued the phenotype, whereas using the mutant MYO6 mRNA (carrying c.2782C>A variant) had no effect. These results strongly suggest the deleterious effect of this variant on the mobility of stereocilia in zebrafish neuromasts, and hence on the auditory system. In the present work, we demonstrated that our algorithm is suitable for the sequential multigenic approach to HL in our cohort. These results highlight the importance of a combined strategy in order to identify candidate variants as well as the in silico and in vivo studies to analyze and prove their pathogenicity and accomplish a better understanding of the mechanisms underlying the physiopathology of the hearing impairment.

Keywords: diagnosis, genetics, hearing loss, in silico analysis, in vivo analysis, WES, zebrafish

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Authors: Elvis Medina, Alejandro Karelovic, Romel Jiménez

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Catalytic ammonia decomposition represents an attractive alternative due to its high H₂ content (17.8% w/w), a product stream free of COₓ, among others; however, challenges need to be addressed for its consolidation as an H₂ chemical storage technology, especially, those focused on the synthesis of efficient bimetallic catalytic systems, as an alternative to the price and scarcity of ruthenium, the most active catalyst reported. In this sense, from the perspective of rational catalyst design, adjusting the main catalytic activity descriptor, a screening of supported catalysts with different compositional settings of cobalt-molybdenum metals is presented to evaluate their effect on the catalytic decomposition rate of ammonia. Subsequently, a kinetic study on the supported monometallic Co and Mo catalysts, as well as on the bimetallic CoMo catalyst with the highest activity is shown. The synthesis of catalysts supported on γ-alumina was carried out using the Charge Enhanced Dry Impregnation (CEDI) method, all with a 5% w/w loading metal. Seeking to maintain uniform dispersion, the catalysts were oxidized and activated (In-situ activation) using a flow of anhydrous air and hydrogen, respectively, under the same conditions: 40 ml min⁻¹ and 5 °C min⁻¹ from room temperature to 600 °C. Catalytic tests were carried out in a fixed-bed reactor, confirming the absence of transport limitations, as well as an Approach to equilibrium (< 1 x 10⁻⁴). The reaction rate on all catalysts was measured between 400 and 500 ºC at 53.09 kPa NH3. The synergy theoretically (DFT) reported for bimetallic catalysts was confirmed experimentally. Specifically, it was observed that the catalyst composed mainly of 75 mol% cobalt proved to be the most active in the experiments, followed by the monometallic cobalt and molybdenum catalysts, in this order of activity as referred to in the literature. A kinetic study was performed at 10.13 – 101.32 kPa NH3 and at four equidistant temperatures between 437 and 475 °C the data were adjusted to an LHHW-type model, which considered the desorption of nitrogen atoms from the active phase surface as the rate determining step (RDS). The regression analysis were carried out under an integral regime, using a minimization algorithm based on SLSQP. The physical meaning of the parameters adjusted in the kinetic model, such as the RDS rate constant (k₅) and the lumped adsorption constant of the quasi-equilibrated steps (α) was confirmed through their Arrhenius and Van't Hoff-type behavior (R² > 0.98), respectively. From an energetic perspective, the activation energy for cobalt, cobalt-molybdenum, and molybdenum was 115.2, 106.8, and 177.5 kJ mol⁻¹, respectively. With this evidence and considering the volcano shape described by the ammonia decomposition rate in relation to the metal composition ratio, the synergistic behavior of the system is clearly observed. However, since characterizations by XRD and TEM were inconclusive, the formation of intermetallic compounds should be still verified using HRTEM-EDS. From this point onwards, our objective is to incorporate parameters into the kinetic expressions that consider both compositional and structural elements and explore how these can maximize or influence H₂ production.

Keywords: CEDI, hydrogen carrier, LHHW, RDS

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Authors: Ibtissem Hosni, Lilia Bennaceur Farah, Saber Mohamed Naceur

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In order to assess the water availability in the soil, it is crucial to have information about soil distributed moisture content; this parameter helps to understand the effect of humidity on the exchange between soil, plant cover and atmosphere in addition to fully understanding the surface processes and the hydrological cycle. On the other hand, aerodynamic roughness length is a surface parameter that scales the vertical profile of the horizontal component of the wind speed and characterizes the surface ability to absorb the momentum of the airflow. In numerous applications of the surface hydrology and meteorology, aerodynamic roughness length is an important parameter for estimating momentum, heat and mass exchange between the soil surface and atmosphere. It is important on this side, to consider the atmosphere factors impact in general, and the natural erosion in particular, in the process of soil evolution and its characterization and prediction of its physical parameters. The study of the induced movements by the wind over soil vegetated surface, either spaced plants or plant cover, is motivated by significant research efforts in agronomy and biology. The known major problem in this side concerns crop damage by wind, which presents a booming field of research. Obviously, most models of soil surface require information about the aerodynamic roughness length and its temporal and spatial variability. We have used a bi-dimensional multi-scale (2D MLS) roughness description where the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each one having a spatial scale using the wavelet transform and the Mallat algorithm to describe natural surface roughness. We have introduced multi-layer aspect of the humidity of the soil surface, to take into account a volume component in the problem of backscattering radar signal. As humidity increases, the dielectric constant of the soil-water mixture increases and this change is detected by microwave sensors. Nevertheless, many existing models in the field of radar imagery, cannot be applied directly on areas covered with vegetation due to the vegetation backscattering. Thus, the radar response corresponds to the combined signature of the vegetation layer and the layer of soil surface. Therefore, the key issue of the numerical estimation of soil moisture is to separate the two contributions and calculate both scattering behaviors of the two layers by defining the scattering of the vegetation and the soil blow. This paper presents a synergistic methodology, and it is for estimating roughness and soil moisture from C-band radar measurements. The methodology adequately represents a microwave/optical model which has been used to calculate the scattering behavior of the aerodynamic vegetation-covered area by defining the scattering of the vegetation and the soil below.

Keywords: aerodynamic, bi-dimensional, vegetation, synergistic

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Authors: Maria Ledinskaya

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This paper examines the Morris Collection Conservation Project at the Sainsbury Centre for Visual Arts in the context of Agile, Lean, and Hybrid project management. It is part case study and part literature review. To date, relatively little has been written about non-traditional project management approaches in heritage conservation. This paper seeks to introduce Agile, Lean, and Hybrid project management concepts from business, software development, and manufacturing fields to museum conservation, by referencing their practical application on a recent museum-based conservation project. The Morris Collection Conservation Project was carried out in 2019-2021 in Norwich, UK, and concerned the remedial conservation of around 150 Abstract Constructivist artworks bequeathed to the Sainsbury Centre for Visual Arts by private collectors Michael and Joyce Morris. The first part introduces the chronological timeline and key elements of the project. It describes a medium-size conservation project of moderate complexity, which was planned and delivered in an environment with multiple known unknowns – unresearched collection, unknown condition and materials, unconfirmed budget. The project was also impacted by the unknown unknowns of the COVID-19 pandemic, such as indeterminate lockdowns, and the need to accommodate social distancing and remote communications. The author, a staff conservator at the Sainsbury Centre who acted as project manager on the Morris Collection Conservation Project, presents an incremental, iterative, and value-based approach to managing a conservation project in an uncertain environment. Subsequent sections examine the project from the point of view of Traditional, Agile, Lean, and Hybrid project management. The author argues that most academic writing on project management in conservation has focussed on a Traditional plan-driven approach – also known as Waterfall project management – which has significant drawbacks in today’s museum environment, due to its over-reliance on prediction-based planning and its low tolerance to change. In the last 20 years, alternative Agile, Lean and Hybrid approaches to project management have been widely adopted in software development, manufacturing, and other industries, although their recognition in the museum sector has been slow. Using examples from the Morris Collection Conservation Project, the author introduces key principles and tools of Agile, Lean, and Hybrid project management and presents a series of arguments on the effectiveness of these alternative methodologies in museum conservation, as well as the ethical and practical challenges to their implementation. These project management approaches are discussed in the context of consequentialist, relativist, and utilitarian developments in contemporary conservation ethics, particularly with respect to change management, bespoke ethics, shared decision-making, and value-based cost-benefit conservation strategy. The author concludes that the Morris Collection Conservation Project had multiple Agile and Lean features which were instrumental to the successful delivery of the project. These key features are identified as distributed decision making, a co-located cross-disciplinary team, servant leadership, focus on value-added work, flexible planning done in shorter sprint cycles, light documentation, and emphasis on reducing procedural, financial, and logistical waste. Overall, the author’s findings point largely in favour of a Hybrid model which combines traditional and alternative project processes and tools to suit the specific needs of the project.

Keywords: project management, conservation, waterfall, agile, lean, hybrid

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Authors: G. Singer, M. Golan

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Providing students with learning disabilities (LD) with extra time to grant them equal access to the exam is a necessary but insufficient condition to compensate for their LD; there should also be a clear indication that the additional time was actually used. For example, if students with LD use more time than students without LD and yet receive lower grades, this may indicate that a different accommodation is required. If they achieve higher grades but use the same amount of time, then the effectiveness of the accommodation has not been demonstrated. The main goal of this study is to evaluate the effect of including parameters related to LD and extended exam time, along with other commonly-used characteristics (e.g., student background and ability measures such as high-school grades), on the ability of ordinal decision-tree algorithms to predict exam performance. We use naturally-occurring data collected from hundreds of undergraduate engineering students. The sub-goals are i) to examine the improvement in prediction accuracy when the indicator of exam performance includes 'actual time used' in addition to the conventional indicator (exam grade) employed in most research; ii) to explore the effectiveness of extended exam time on exam performance for different courses and for LD students with different profiles (i.e., sets of characteristics). This is achieved by using the patterns (i.e., subgroups) generated by the algorithms to identify pairs of subgroups that differ in just one characteristic (e.g., course or type of LD) but have different outcomes in terms of exam performance (grade and time used). Since grade and time used to exhibit an ordering form, we propose a method based on ordinal decision-trees, which applies a weighted information-gain ratio (WIGR) measure for selecting the classifying attributes. Unlike other known ordinal algorithms, our method does not assume monotonicity in the data. The proposed WIGR is an extension of an information-theoretic measure, in the sense that it adjusts to the case of an ordinal target and takes into account the error severity between two different target classes. Specifically, we use ordinal C4.5, random-forest, and AdaBoost algorithms, as well as an ensemble technique composed of ordinal and non-ordinal classifiers. Firstly, we find that the inclusion of LD and extended exam-time parameters improves prediction of exam performance (compared to specifications of the algorithms that do not include these variables). Secondly, when the indicator of exam performance includes 'actual time used' together with grade (as opposed to grade only), the prediction accuracy improves. Thirdly, our subgroup analyses show clear differences in the effect of extended exam time on exam performance among different courses and different student profiles. From a methodological perspective, we find that the ordinal decision-tree based algorithms outperform their conventional, non-ordinal counterparts. Further, we demonstrate that the ensemble-based approach leverages the strengths of each type of classifier (ordinal and non-ordinal) and yields better performance than each classifier individually.

Keywords: actual exam time usage, ensemble learning, learning disabilities, ordinal classification, time extension

Procedia PDF Downloads 93

Authors: Gabriella Zarlenga, Martha L. Hall

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Introduction: Premature infants are at risk for neurodevelopmental deficits and hospital readmissions, which can increase the financial burden on the health care system and families. Kangaroo care (skin-to-skin contact) is a practice that can improve preterm infant health outcomes. Preterm infants can acquire adequate body temperature, heartbeat, and breathing regulation through lying directly on the mother’s abdomen and in between her breasts. Due to some infant’s condition, kangaroo care is not a feasible intervention. The purpose of this proof-of-concept research project is to create a device which simulates skin-to-skin contact for pre-term infants not eligible for kangaroo care, with the aim of promoting baby’s health outcomes, reducing the incidence of serious neonatal and early childhood illnesses, and/or improving cognitive, social and emotional aspects of development. Methods: The study design is a proof-of-concept based on a three-phase approach; (1) observational study and data analysis of the standard of care for 2 groups of pre-term infants, (2) design and concept development of a novel device for pre-term infants not currently eligible for standard kangaroo care, and (3) prototyping, laboratory testing, and evaluation of the novel device in comparison to current assessment parameters of kangaroo care. A single center study will be conducted in an area hospital offering Level III neonatal intensive care. Eligible participants include newborns born premature (28-30 weeks of age) admitted to the NICU. The study design includes 2 groups: a control group receiving standard kangaroo care and an experimental group not eligible for kangaroo care. Based on behavioral analysis of observational video data collected in the NICU, the device will be created to simulate mother’s body using electrical components in a thermoplastic polymer housing covered in silicone. It will be designed with a microprocessor that controls simulated respiration, heartbeat, and body temperature of the 'simulated caregiver' by using a pneumatic lung, vibration sensors (heartbeat), pressure sensors (weight/position), and resistive film to measure temperature. A slight contour of the simulator surface may be integrated to help position the infant correctly. Control and monitoring of the skin-to-skin contact simulator would be performed locally by an integrated touchscreen. The unit would have built-in Wi-Fi connectivity as well as an optional Bluetooth connection in which the respiration and heart rate could be synced with a parent or caregiver. A camera would be integrated, allowing a video stream of the infant in the simulator to be streamed to a monitoring location. Findings: Expected outcomes are stabilization of respiratory and cardiac rates, thermoregulation of those infants not eligible for skin to skin contact with their mothers, and real time mother Bluetooth to the device to mimic the experience in the womb. Results of this study will benefit clinical practice by creating a new standard of care for premature neonates in the NICU that are deprived of skin to skin contact due to various health restrictions.

Keywords: kangaroo care, wearable technology, pre-term infants, medical design

Procedia PDF Downloads 150

Authors: Shenlun Chen, Leonard Wee

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Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

Procedia PDF Downloads 128

Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

Procedia PDF Downloads 110

Authors: Zhenmin Tao, Jasper De Smet, Koen Laurijssen, Jeroen Stuyts, Sonja Sioncke

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Today, the quality of knowledge management (KM)become one of the underpinning factors in the success of an organization, as it determines the effectiveness of capitalizing the organization’s knowledge. Overall, KMin an organization consists of five aspects: (knowledge) creation, validation, presentation, distribution, and application. Among others, KM in research institutes is considered as the cornerstone as their activities cover all five aspects. Furthermore, KM in a research institute facilitates the steering committee to envision the future roadmap, identify knowledge gaps, and make decisions on future research directions. Likewise, KMis even more challenging in industrial research institutes. From a technical perspective, technology advancement in the past decades calls for combinations of breadth and depth in expertise that poses challenges in talent acquisition and, therefore, knowledge creation. From a regulatory perspective, the strict intellectual property protection from industry collaborators and/or the contractual agreements made by possible funding authoritiesform extra barriers to knowledge validation, presentation, and distribution. From a management perspective, seamless KM activities are only guaranteed by inter-disciplinary talents that combine technical background knowledge, management skills, and leadership, let alone international vision. From a financial perspective, the long feedback period of new knowledge, together with the massive upfront investment costs and low reusability of the fixed assets, lead to low RORC (return on research capital) that jeopardize KM practice. In this study, we aim to address the challenges, practices, and opportunitiesof KM in Flanders Make – a leading European research institute specialized in the manufacturing industry. In particular, the analyses encompass an internal KM project which involves functionalities ranging from management to technical domain experts. This wide range of functionalities provides comprehensive empirical evidence on the challenges and practices w.r.t.the abovementioned KMaspects. Then, we ground our analysis onto the critical dimensions ofKM–individuals, socio‐organizational processes, and technology. The analyses have three steps: First, we lay the foundation and define the environment of this study by briefing the KM roles played by different functionalities in Flanders Make. Second, we zoom in to the CoreLab MotionS where the KM project is located. In this step, given the technical domains covered by MotionS products, the challenges in KM will be addressed w.r.t. the five KM aspects and three critical dimensions. Third, by detailing the objectives, practices, results, and limitations of the MotionSKMproject, we justify the practices and opportunities derived in the execution ofKMw.r.t. the challenges addressed in the second step. The results of this study are twofold: First, a KM framework that consolidates past knowledge is developed. A library based on this framework can, therefore1) overlook past research output, 2) accelerate ongoing research activities, and 3) envision future research projects. Second, the challenges inKM on both individual (actions) level and socio-organizational level (e.g., interactions between individuals)are identified. By doing so, suggestions and guidelines will be provided in KM in the context of industrial research institute. To this end, the results in this study are reflected towards the findings in existing literature.

Keywords: technical knowledge management framework, industrial research institutes, individual knowledge management, socio-organizational knowledge management.

Procedia PDF Downloads 100

Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yonggang Qian, Ning Wang

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Knowledge of land surface temperature (LST) is of crucial important in energy balance studies and environment modeling. Satellite thermal infrared (TIR) imagery is the primary source for retrieving LST at the regional and global scales. Due to the combination of atmosphere and land surface of received radiance by TIR sensors, atmospheric effect correction has to be performed to remove the atmospheric transmittance and upwelling radiance. Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) provides measurements every 15 minutes in 12 spectral channels covering from visible to infrared spectrum at fixed view angles with 3km pixel size at nadir, offering new and unique capabilities for LST, LSE measurements. However, due to its high temporal resolution, the atmosphere correction could not be performed with radiosonde profiles or reanalysis data since these profiles are not available at all SEVIRI TIR image acquisition times. To solve this problem, a two-part six-parameter semi-empirical diurnal temperature cycle (DTC) model has been applied to the temporal interpolation of ECMWF reanalysis data. Due to the fact that the DTC model is underdetermined with ECMWF data at four synoptic times (UTC times: 00:00, 06:00, 12:00, 18:00) in one day for each location, some approaches are adopted in this study. It is well known that the atmospheric transmittance and upwelling radiance has a relationship with water vapour content (WVC). With the aid of simulated data, the relationship could be determined under each viewing zenith angle for each SEVIRI TIR channel. Thus, the atmospheric transmittance and upwelling radiance are preliminary removed with the aid of instantaneous WVC, which is retrieved from the brightness temperature in the SEVIRI channels 5, 9 and 10, and a group of the brightness temperatures for surface leaving radiance (Tg) are acquired. Subsequently, a group of the six parameters of the DTC model is fitted with these Tg by a Levenberg-Marquardt least squares algorithm (denoted as DTC model 1). Although the retrieval error of WVC and the approximate relationships between WVC and atmospheric parameters would induce some uncertainties, this would not significantly affect the determination of the three parameters, td, ts and β (β is the angular frequency, td is the time where the Tg reaches its maximum, ts is the starting time of attenuation) in DTC model. Furthermore, due to the large fluctuation in temperature and the inaccuracy of the DTC model around sunrise, SEVIRI measurements from two hours before sunrise to two hours after sunrise are excluded. With the knowledge of td , ts, and β, a new DTC model (denoted as DTC model 2) is accurately fitted again with these Tg at UTC times: 05:57, 11:57, 17:57 and 23:57, which is atmospherically corrected with ECMWF data. And then a new group of the six parameters of the DTC model is generated and subsequently, the Tg at any given times are acquired. Finally, this method is applied to SEVIRI data in channel 9 successfully. The result shows that the proposed method could be performed reasonably without assumption and the Tg derived with the improved method is much more consistent with that from radiosonde measurements.

Keywords: atmosphere correction, diurnal temperature cycle model, land surface temperature, SEVIRI

Procedia PDF Downloads 259

Authors: Andreas Kohlhepp, Gerrit Schatte, Wieland Christoph, Spliethoff Hartmut

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In recent years the research of heat transfer phenomena of water and other working fluids near the critical point experiences a growing interest for power engineering applications. To match the highly volatile characteristics of renewable energies, conventional power plants need to shift towards flexible operation. This requires speeding up the load change dynamics of steam generators and their heating surfaces near the critical point. In dynamic load transients, both a high heat flux with an unfavorable ratio to the mass flux and a high difference in fluid and wall temperatures, may cause problems. It may lead to deteriorated heat transfer (at supercritical pressures), dry-out or departure from nucleate boiling (at subcritical pressures), all cases leading to an extensive rise of temperatures. For relevant technical applications, the heat transfer coefficients need to be predicted correctly in case of transient scenarios to prevent damage to the heated surfaces (membrane walls, tube bundles or fuel rods). In transient processes, the state of the art method of calculating the heat transfer coefficients is using a multitude of different steady-state correlations for the momentarily existing local parameters for each time step. This approach does not necessarily reflect the different cases that may lead to a significant variation of the heat transfer coefficients and shows gaps in the individual ranges of validity. An algorithm was implemented to calculate the transient behavior of steam generators during load changes. It is used to assess existing correlations for transient heat transfer calculations. It is also desirable to validate the calculation using experimental data. By the use of a new full-scale supercritical thermo-hydraulic test rig, experimental data is obtained to describe the transient phenomena under dynamic boundary conditions as mentioned above and to serve for validation of transient steam generator calculations. Aiming to improve correlations for the prediction of the onset of deteriorated heat transfer in both, stationary and transient cases the test rig was specially designed for this task. It is a closed loop design with a directly electrically heated evaporation tube, the total heating power of the evaporator tube and the preheater is 1MW. To allow a big range of parameters, including supercritical pressures, the maximum pressure rating is 380 bar. The measurements contain the most important extrinsic thermo-hydraulic parameters. Moreover, a high geometric resolution allows to accurately predict the local heat transfer coefficients and fluid enthalpies.

Keywords: departure from nucleate boiling, deteriorated heat transfer, dryout, supercritical working fluid, transient operation of steam generators

Procedia PDF Downloads 212

Authors: Nicoly Coelho, Eduardo Vieira Vilas Boas, Paulo Orestes Formigoni

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Faced with the remarkable developments in the various segments of modern engineering, provided by the increasing technological development, professionals of all educational areas need to overcome the difficulties generated due to the good understanding of those who are starting their academic journey. Aiming to overcome these difficulties, this article aims at an introduction to the basic study of numerical methods applied to fluid mechanics and thermodynamics, demonstrating the modeling and simulations with its substance, and a detailed explanation of the fundamental numerical solution for the use of finite difference method, using SCILAB, a free software easily accessible as it is free and can be used for any research center or university, anywhere, both in developed and developing countries. It is known that the Computational Fluid Dynamics (CFD) is a necessary tool for engineers and professionals who study fluid mechanics, however, the teaching of this area of knowledge in undergraduate programs faced some difficulties due to software costs and the degree of difficulty of mathematical problems involved in this way the matter is treated only in postgraduate courses. This work aims to bring the use of DFC low cost in teaching Transport Phenomena for graduation analyzing a small classic case of fundamental thermodynamics with Scilab® program. The study starts from the basic theory involving the equation the partial differential equation governing heat transfer problem, implies the need for mastery of students, discretization processes that include the basic principles of series expansion Taylor responsible for generating a system capable of convergence check equations using the concepts of Sassenfeld, finally coming to be solved by Gauss-Seidel method. In this work we demonstrated processes involving both simple problems solved manually, as well as the complex problems that required computer implementation, for which we use a small algorithm with less than 200 lines in Scilab® in heat transfer study of a heated plate in rectangular shape on four sides with different temperatures on either side, producing a two-dimensional transport with colored graphic simulation. With the spread of computer technology, numerous programs have emerged requiring great researcher programming skills. Thinking that this ability to program DFC is the main problem to be overcome, both by students and by researchers, we present in this article a hint of use of programs with less complex interface, thus enabling less difficulty in producing graphical modeling and simulation for DFC with an extension of the programming area of experience for undergraduates.

Keywords: numerical methods, finite difference method, heat transfer, Scilab

Procedia PDF Downloads 368

Authors: Alessandro Evangelista, Vito M. Manghisi, Michele Gattullo, Enricoandrea Laviola

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In this work, we propose a custom visualization technique for Out-Of-View-Objects in Virtual and Augmented Reality applications using Head Mounted Displays. In the last two decades, Augmented Reality (AR) and Virtual Reality (VR) technologies experienced a remarkable growth of applications for navigation, interaction, and collaboration in different types of environments, real or virtual. Both environments can be potentially very complex, as they can include many virtual objects located in different places. Given the natural limitation of the human Field of View (about 210° horizontal and 150° vertical), humans cannot perceive objects outside this angular range. Moreover, despite recent technological advances in AR e VR Head-Mounted Displays (HMDs), these devices still suffer from a limited Field of View, especially regarding Optical See-Through displays, thus greatly amplifying the challenge of visualizing out-of-view objects. This problem is not negligible when the user needs to be aware of the number and the position of the out-of-view objects in the environment. For instance, during a maintenance operation on a construction site where virtual objects serve to improve the dangers' awareness. Providing such information can enhance the comprehension of the scene, enable fast navigation and focused search, and improve users' safety. In our research, we investigated how to represent out-of-view-objects in HMD User Interfaces (UI). Inspired by commercial video games such as Call of Duty Modern Warfare, we designed a customized Compass. By exploiting the Unity 3D graphics engine, we implemented our custom solution that can be used both in AR and VR environments. The Compass Bar consists of a graduated bar (in degrees) at the top center of the UI. The values of the bar range from -180 (far left) to +180 (far right), the zero is placed in front of the user. Two vertical lines on the bar show the amplitude of the user's field of view. Every virtual object within the scene is represented onto the compass bar as a specific color-coded proxy icon (a circular ring with a colored dot at its center). To provide the user with information about the distance, we implemented a specific algorithm that increases the size of the inner dot as the user approaches the virtual object (i.e., when the user reaches the object, the dot fills the ring). This visualization technique for out-of-view objects has some advantages. It allows users to be quickly aware of the number and the position of the virtual objects in the environment. For instance, if the compass bar displays the proxy icon at about +90, users will immediately know that the virtual object is to their right and so on. Furthermore, by having qualitative information about the distance, users can optimize their speed, thus gaining effectiveness in their work. Given the small size and position of the Compass Bar, our solution also helps lessening the occlusion problem thus increasing user acceptance and engagement. As soon as the lockdown measures will allow, we will carry out user-tests comparing this solution with other state-of-the-art existing ones such as 3D Radar, SidebARs and EyeSee360.

Keywords: augmented reality, situation awareness, virtual reality, visualization design

Procedia PDF Downloads 115

Authors: Silvia D. Vaca, Benjamin J. Kuo, Joao Ricardo Nickenig Vissoci, Catherine A. Staton, Linda W. Xu, Michael Muhumuza, Hussein Ssenyonjo, John Mukasa, Joel Kiryabwire, Henry E. Rice, Gerald A. Grant, Michael M. Haglund

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Background: Patients with traumatic brain injury (TBI) can develop rapid neurological deterioration from swelling and intracranial hematomas, which can result in focal tissue ischemia, brain compression, and herniation. Moreover, delays in management increase the risk of secondary brain injury from hypoxemia and hypotension. Therefore, in TBI patients with subdural hematomas (SDHs) and epidural hematomas (EDHs), surgical intervention is both necessary and time sensitive. Significant delays are seen along the care continuum in low- and middle-income countries (LMICs) largely due to limited healthcare capacity to address the disproportional rates of TBI in Sub Saharan Africa (SSA). While many LMICs have subsidized systems to offset surgical costs, the burden of securing funds by the patients for medications, supplies, and CT diagnostics poses a significant challenge to timely surgical interventions. In Kampala Uganda, the challenge of obtaining timely CT scans is twofold: logistical and financial barriers. These bottlenecks contribute significantly to the care continuum delays and are associated with poor TBI outcomes. Objective: The objectives of this study are to 1) describe the temporal delays through a modified three delays model that fits the context of neurosurgical interventions for TBI patients in Kampala and 2) investigate the association between delays and mortality. Methods: Prospective data were collected for 563 TBI patients presenting to a tertiary hospital in Kampala from 1 June – 30 November 2016. Four time intervals were constructed along five time points: injury, hospital arrival, neurosurgical evaluation, CT results, and definitive surgery. Time interval differences among mild, moderate and severe TBI and their association with mortality were analyzed. Results: The mortality rate of all TBI patients presenting to MNRH was 9.6%, which ranged from 4.7% for mild and moderate TBI patients receiving surgery to 81.8% for severe TBI patients who failed to receive surgery. The duration from injury to surgery varied considerably across TBI severity with the largest gap seen between mild TBI (174 hours) and severe TBI (69 hours) patients. Further analysis revealed care continuum differences for interval 3 (neurosurgical evaluation to CT result) and 4 (CT result to surgery) between severe TBI patients (7 hours for interval 3 and 24 hours for interval 4) and mild TBI patients (19 hours for interval 3, and 96 hours for interval 4). These post-arrival delays were associated with mortality for mild (p=0.05) and moderate TBI (p=0.03) patients. Conclusions: To our knowledge, this is the first analysis using a modified 'three delays' framework to analyze the care continuum of TBI patients in Uganda from injury to surgery. We found significant associations between delays and mortality for mild and moderate TBI patients. As it currently stands, poorer outcomes were observed for these mild and moderate TBI patients who were managed non-operatively or failed to receive surgery while surgical services were shunted to more severely ill patients. While well intentioned, high mortality rates were still observed for the severe TBI patients managed surgically. These results suggest the need for future research to optimize triage practices, understand delay contributors, and improve pre-hospital logistical referral systems.

Keywords: care continuum, global neurosurgery, Kampala Uganda, LMIC, Mulago, traumatic brain injury

Procedia PDF Downloads 198

Authors: James Brown, Stella Kortekaas, Ian Finnie, George Zhang, Christine Devine, Neil Healy

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The use of GIS as an analysis tool for engineering decision making is now best practice in the offshore industry. GIS enables multidisciplinary data integration, analysis and visualisation which allows the presentation of large and intricate datasets in a simple map-interface accessible to all project stakeholders. Presenting integrated geoscience and geotechnical data in GIS enables decision makers to be well-informed. This paper is a successful case study of how GIS spatial analysis techniques were applied to help select the most favourable pipeline route. Routing a pipeline through any natural environment has numerous obstacles, whether they be topographical, geological, engineering or financial. Where the pipeline is subjected to external hydrostatic water pressure and is carrying pressurised hydrocarbons, the requirement to safely route the pipeline through hazardous terrain becomes absolutely paramount. This study illustrates how the application of modern, GIS-based pipeline routing techniques enabled the identification of a single most-favourable pipeline route crossing of a challenging seabed terrain. Conventional approaches to pipeline route determination focus on manual avoidance of primary constraints whilst endeavouring to minimise route length. Such an approach is qualitative, subjective and is liable to bias towards the discipline and expertise that is involved in the routing process. For very short routes traversing benign seabed topography in shallow water this approach may be sufficient, but for deepwater geohazardous sites, the need for an automated, multi-criteria, and quantitative approach is essential. This study combined multiple routing constraints using modern least-cost-routing algorithms deployed in GIS, hitherto unachievable with conventional approaches. The least-cost-routing procedure begins with the assignment of geocost across the study area. Geocost is defined as a numerical penalty score representing hazard posed by each routing constraint (e.g. slope angle, rugosity, vulnerability to debris flows) to the pipeline. All geocosted routing constraints are combined to generate a composite geocost map that is used to compute the least geocost route between two defined terminals. The analyses were applied to select the most favourable pipeline route for a potential gas development in deep water. The study area is geologically complex with a series of incised, potentially active, canyons carved into a steep escarpment, with evidence of extensive debris flows. A similar debris flow in the future could cause significant damage to a poorly-placed pipeline. Protruding inter-canyon spurs offer lower-gradient options for ascending an escarpment but the vulnerability of periodic failure of these spurs is not well understood. Close collaboration between geoscientists, pipeline engineers, geotechnical engineers and of course the gas export pipeline operator guided the analyses and assignment of geocosts. Shorter route length, less severe slope angles, and geohazard avoidance were the primary drivers in identifying the most favourable route.

Keywords: geocost, geohazard, pipeline route determination, pipeline route optimisation, spatial analysis

Procedia PDF Downloads 389

Authors: Amber Dhoot, Tarush Gupta, Andrea Gurr, William Jenkins, Sandro Pietrunti, Alexis Tang

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Background: The COVID-19 pandemic has driven pharmacovigilance towards a new paradigm. Nowadays, more people than ever before are recognising and reporting adverse reactions from medications, treatments, and vaccines. In the modern era, with over 3.8 billion users, social media has become the most accessible medium for people to voice their opinions and so provides an opportunity to engage with more patient-centric and accessible pharmacovigilance. However, the pharmaceutical industry has been slow to incorporate social media into its modern pharmacovigilance strategy. This project aims to make social media a more effective tool in pharmacovigilance, and so reduce drug costs, improve drug safety and improve patient outcomes. This will be achieved by firstly uncovering and categorising the barriers facing the widespread adoption of social media in pharmacovigilance. Following this, the potential opportunities of social media will be explored. We will then propose realistic, practical recommendations to make social media a more effective tool for pharmacovigilance. Methodology: A comprehensive systematic literature review was conducted to produce a categorised summary of these barriers. This was followed by conducting 11 semi-structured interviews with pharmacovigilance experts to confirm the literature review findings whilst also exploring the unpublished and real-life challenges faced by those in the pharmaceutical industry. Finally, a survey of the general public (n = 112) ascertained public knowledge, perception, and opinion regarding the use of their social media data for pharmacovigilance purposes. This project stands out by offering perspectives from the public and pharmaceutical industry that fill the research gaps identified in the literature review. Results: Our results gave rise to several key analysis points. Firstly, inadequacies of current Natural Language Processing algorithms hinder effective pharmacovigilance data extraction from social media, and where data extraction is possible, there are significant questions over its quality. Social media also contains a variety of biases towards common drugs, mild adverse drug reactions, and the younger generation. Additionally, outdated regulations for social media pharmacovigilance do not align with new, modern General Data Protection Regulations (GDPR), creating ethical ambiguity about data privacy and level of access. This leads to an underlying mindset of avoidance within the pharmaceutical industry, as firms are disincentivised by the legal, financial, and reputational risks associated with breaking ambiguous regulations. Conclusion: Our project uncovered several barriers that prevent effective pharmacovigilance on social media. As such, social media should be used to complement traditional sources of pharmacovigilance rather than as a sole source of pharmacovigilance data. However, this project adds further value by proposing five practical recommendations that improve the effectiveness of social media pharmacovigilance. These include: prioritising health-orientated social media; improving technical capabilities through investment and strategic partnerships; setting clear regulatory guidelines using multi-stakeholder processes; creating an adverse drug reaction reporting interface inbuilt into social media platforms; and, finally, developing educational campaigns to raise awareness of the use of social media in pharmacovigilance. Implementation of these recommendations would speed up the efficient, ethical, and systematic adoption of social media in pharmacovigilance.

Keywords: adverse drug reaction, drug safety, pharmacovigilance, social media

Procedia PDF Downloads 70

Authors: Lucia Billeci, Gennaro Tartarisco, Maurizio Varanini

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Fetal cardiac monitoring by fetal electrocardiogram (fECG) can provide significant clinical information about the healthy condition of the fetus. Despite this potentiality till now the use of fECG in clinical practice has been quite limited due to the difficulties in its measuring. The recovery of fECG from the signals acquired non-invasively by using electrodes placed on the maternal abdomen is a challenging task because abdominal signals are a mixture of several components and the fetal one is very weak. This paper presents an approach for fECG extraction from abdominal maternal recordings, which exploits the characteristics of pseudo-periodicity of fetal ECG. It consists of devising a quality index (fQI) for fECG and of finding the linear combinations of preprocessed abdominal signals, which maximize these fQI (quality index optimization - QIO). It aims at improving the performances of the most commonly adopted methods for fECG extraction, usually based on maternal ECG (mECG) estimating and canceling. The procedure for the fECG extraction and fetal QRS (fQRS) detection is completely unsupervised and based on the following steps: signal pre-processing; maternal ECG (mECG) extraction and maternal QRS detection; mECG component approximation and canceling by weighted principal component analysis; fECG extraction by fQI maximization and fetal QRS detection. The proposed method was compared with our previously developed procedure, which obtained the highest at the Physionet/Computing in Cardiology Challenge 2013. That procedure was based on removing the mECG from abdominal signals estimated by a principal component analysis (PCA) and applying the Independent component Analysis (ICA) on the residual signals. Both methods were developed and tuned using 69, 1 min long, abdominal measurements with fetal QRS annotation of the dataset A provided by PhysioNet/Computing in Cardiology Challenge 2013. The QIO-based and the ICA-based methods were compared in analyzing two databases of abdominal maternal ECG available on the Physionet site. The first is the Abdominal and Direct Fetal Electrocardiogram Database (ADdb) which contains the fetal QRS annotations thus allowing a quantitative performance comparison, the second is the Non-Invasive Fetal Electrocardiogram Database (NIdb), which does not contain the fetal QRS annotations so that the comparison between the two methods can be only qualitative. In particular, the comparison on NIdb was performed defining an index of quality for the fetal RR series. On the annotated database ADdb the QIO method, provided the performance indexes Sens=0.9988, PPA=0.9991, F1=0.9989 overcoming the ICA-based one, which provided Sens=0.9966, PPA=0.9972, F1=0.9969. The comparison on NIdb was performed defining an index of quality for the fetal RR series. The index of quality resulted higher for the QIO-based method compared to the ICA-based one in 35 records out 55 cases of the NIdb. The QIO-based method gave very high performances with both the databases. The results of this study foresees the application of the algorithm in a fully unsupervised way for the implementation in wearable devices for self-monitoring of fetal health.

Keywords: fetal electrocardiography, fetal QRS detection, independent component analysis (ICA), optimization, wearable

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Authors: Sudipto Sarkar, Anamika Paul

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Pseudoplastic (n<1, n is the power index) fluids have great importance in food, pharmaceutical and chemical process industries which require a lot of attention. Unfortunately, due to its complex flow behavior inadequate research works can be found even in laminar flow regime. A practical problem is solved in the present research work by numerical simulation where we tried to control the vortex shedding from a square cylinder using a horizontal splitter plate placed at the downstream flow region. The position of the plate is at the centerline of the cylinder with varying distance from the cylinder to calculate the critical gap-ratio. If the plate is placed inside this critical gap, the vortex shedding from the cylinder suppressed completely. The Reynolds number considered here is in unsteady laminar vortex shedding regime, Re = 100 (Re = U∞a/ν, where U∞ is the free-stream velocity of the flow, a is the side of the cylinder and ν is the maximum value of kinematic viscosity of the fluid). Flow behavior has been studied for three different gap-ratios (G/a = 2, 2.25 and 2.5, where G is the gap between cylinder and plate) and for a fluid with three different flow behavior indices (n =1, 0.8 and 0.5). The flow domain is constructed using Gambit 2.2.30 and this software is also used to generate the mesh and to impose the boundary conditions. For G/a = 2, the domain size is considered as 37.5a × 16a with 316 × 208 grid points in the streamwise and flow-normal directions respectively after a thorough grid independent study. Fine and equal grid spacing is used close to the geometry to capture the vortices shed from the cylinder and the boundary layer developed over the flat plate. Away from the geometry meshes are unequal in size and stretched out. For other gap-ratios, proportionate domain size and total grid points are used with similar kind of mesh distribution. Velocity inlet (u = U∞), pressure outlet (Neumann condition), symmetry (free-slip boundary condition) at upper and lower domain boundary conditions are used for the simulation. Wall boundary condition (u = v = 0) is considered both on the cylinder and the splitter plate surfaces. Discretized forms of fully conservative 2-D unsteady Navier Stokes equations are then solved by Ansys Fluent 14.5. SIMPLE algorithm written in finite volume method is selected for this purpose which is a default solver inculcate in Fluent. The results obtained for Newtonian fluid flow agree well with previous works supporting Fluent’s usefulness in academic research. A thorough analysis of instantaneous and time-averaged flow fields are depicted both for Newtonian and pseudoplastic fluid flow. It has been observed that as the value of n reduces the stretching of shear layers also reduce and these layers try to roll up before the plate. For flow with high pseudoplasticity (n = 0.5) the nature of vortex shedding changes and the value of critical gap-ratio reduces. These are the remarkable findings for laminar periodic vortex shedding regime in pseudoplastic flow environment.

Keywords: CFD, pseudoplastic fluid flow, wake-boundary layer interactions, critical gap-ratio

Procedia PDF Downloads 104

Authors: Abhinav Singh

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Point Of Sale (POS) malwares have been stealing the limelight this year. They have been the elemental factor in some of the biggest breaches uncovered in past couple of years. Some of them include • Target: A Retail Giant reported close to 40 million credit card data being stolen • Home Depot : A home product Retailer reported breach of close to 50 million credit records • Kmart: A US retailer recently announced breach of 800 thousand credit card details. Alone in 2014, there have been reports of over 15 major breaches of payment systems around the globe. Memory scrapping malwares infecting the point of sale devices have been the lethal weapon used in these attacks. These malwares are capable of reading the payment information from the payment device memory before they are being encrypted. Later on these malwares send the stolen details to its parent server. These malwares are capable of recording all the critical payment information like the card number, security number, owner etc. All these information are delivered in raw format. This Talk will cover the aspects of what happens after these details have been sent to the malware authors. The entire ecosystem of credit card frauds can be broadly classified into these three steps: • Purchase of raw details and dumps • Converting them to plastic cash/cards • Shop! Shop! Shop! The focus of this talk will be on the above mentioned points and how they form an organized network of cyber-crime. The first step involves buying and selling of the stolen details. The key point to emphasize are : • How is this raw information been sold in the underground market • The buyer and seller anatomy • Building your shopping cart and preferences • The importance of reputation and vouches • Customer support and replace/refunds These are some of the key points that will be discussed. But the story doesn’t end here. As of now the buyer only has the raw card information. How will this raw information be converted to plastic cash? Now comes in picture the second part of this underground economy where-in these raw details are converted into actual cards. There are well organized services running underground that can help you in converting these details into plastic cards. We will discuss about this technique in detail. At last, the final step involves shopping with the stolen cards. The cards generated with the stolen details can be easily used to swipe-and-pay for purchased goods at different retail shops. Usually these purchases are of expensive items that have good resale value. Apart from using the cards at stores, there are underground services that lets you deliver online orders to their dummy addresses. Once the package is received it will be delivered to the original buyer. These services charge based on the value of item that is being delivered. The overall underground ecosystem of credit card fraud works in a bulletproof way and it involves people working in close groups and making heavy profits. This is a brief summary of what I plan to present at the talk. I have done an extensive research and have collected good deal of material to present as samples. Some of them include: • List of underground forums • Credit card dumps • IRC chats among these groups • Personal chat with big card sellers • Inside view of these forum owners. The talk will be concluded by throwing light on how these breaches are being tracked during investigation. How are credit card breaches tracked down and what steps can financial institutions can build an incidence response over it.

Keywords: POS mawalre, credit card frauds, enterprise security, underground ecosystem

Procedia PDF Downloads 431

Authors: Nutcha Taneepanichskul, Helen C. Hailes, Mark Miodownik

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Plastic waste has emerged as a critical global environmental challenge, primarily driven by the prevalent use of conventional plastics derived from petrochemical refining and manufacturing processes in modern packaging. While these plastics serve vital functions, their persistence in the environment post-disposal poses significant threats to ecosystems. Addressing this issue necessitates approaches, one of which involves the development of biodegradable plastics designed to degrade under controlled conditions, such as industrial composting facilities. It is imperative to note that compostable plastics are engineered for degradation within specific environments and are not suited for uncontrolled settings, including natural landscapes and aquatic ecosystems. The full benefits of compostable packaging are realized when subjected to industrial composting, preventing environmental contamination and waste stream pollution. Therefore, effective sorting technologies are essential to enhance composting rates for these materials and diminish the risk of contaminating recycling streams. In this study, it leverage hyperspectral imaging technology (HSI) coupled with advanced machine learning algorithms to accurately identify various types of plastics, encompassing conventional variants like Polyethylene terephthalate (PET), Polypropylene (PP), Low density polyethylene (LDPE), High density polyethylene (HDPE) and biodegradable alternatives such as Polybutylene adipate terephthalate (PBAT), Polylactic acid (PLA), and Polyhydroxyalkanoates (PHA). The dataset is partitioned into three subsets: a training dataset comprising uncontaminated conventional and biodegradable plastics, a validation dataset encompassing contaminated plastics of both types, and a testing dataset featuring real-world packaging items in both pristine and contaminated states. Five distinct machine learning algorithms, namely Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Logistic Regression, and Decision Tree Algorithm, were developed and evaluated for their classification performance. Remarkably, the Logistic Regression and CNN model exhibited the most promising outcomes, achieving a perfect accuracy rate of 100% for the training and validation datasets. Notably, the testing dataset yielded an accuracy exceeding 80%. The successful implementation of this sorting technology within recycling and composting facilities holds the potential to significantly elevate recycling and composting rates. As a result, the envisioned circular economy for plastics can be established, thereby offering a viable solution to mitigate plastic pollution.

Keywords: biodegradable plastics, sorting technology, hyperspectral imaging technology, machine learning algorithms

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Authors: Rigas Kotsakis, Nikolaos Tsigilis, Vasilis Grammatikopoulos, Evridiki Zachopoulou

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During the last decade, Greece has faced an unprecedented financial crisis, affecting various aspects and functionalities of Higher Education. Besides the restricted funding of academic institutions, the students and their families encountered economical difficulties that undoubtedly influenced the effective completion of their studies. In this context, a fairly large number of students in Alexander campus of International Hellenic University (IHU) delay, interrupt, or even abandon their studies, especially when they come from low-income families, belong to sensitive social or special needs groups, they have different cultural origins, etc. For this reason, a European project, named “Umbrella”, was initiated aiming at providing the necessary psychological support and counseling, especially to disadvantaged students, towards the completion of their studies. To this end, a network of various academic members (academic staff and students) from IHU, namely iMentor, were implicated in different roles. Specifically, experienced academic staff trained students to serve as intermediate links for the integration and educational support of students that fall into the aforementioned sensitive social groups and face problems for the completion of their studies. The main idea of the project is held upon its person-centered character, which facilitates direct student-to-student communication without the intervention of the teaching staff. The backbone of the iMentors network are senior students that face no problem in their academic life and volunteered for this project. It should be noted that there is a provision from the Umbrella structure for substantial and ethical rewards for their engagement. In this context, a well-defined, stringent methodology was implemented for the evaluation of the extent of the problem in IHU and the detection of the profile of the “candidate” disadvantaged students. The first phase included two steps, (a) data collection and (b) data cleansing/ preprocessing. The first step involved the data collection process from the Secretary Services of all Schools in IHU, from 1980 to 2019, which resulted in 96.418 records. The data set included the School name, the semester of studies, a student enrolling criteria, the nationality, the graduation year or the current, up-to-date academic state (still studying, delayed, dropped off, etc.). The second step of the employed methodology involved the data cleansing/preprocessing because of the existence of “noisy” data, missing and erroneous values, etc. Furthermore, several assumptions and grouping actions were imposed to achieve data homogeneity and an easy-to-interpret subsequent statistical analysis. Specifically, the duration of 40 years recording was limited to the last 15 years (2004-2019). In 2004 the Greek Technological Institutions were evolved into Higher Education Universities, leading into a stable and unified frame of graduate studies. In addition, the data concerning active students were excluded from the analysis since the initial processing effort was focused on the detection of factors/variables that differentiated graduate and deleted students. The final working dataset included 21.432 records with only two categories of students, those that have a degree and those who abandoned their studies. Findings of the first phase are presented across faculties and further discussed.

Keywords: higher education, students support, economic crisis, mentoring

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Authors: Fouzia Arif, Arif S. Mohammad, Hifsa Altaf, Lubna Raees

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Introduction: The term "disability", refers to any condition that impedes the completion of daily tasks using traditional methods. In developing countries like Pakistan, disable population is usually excluded from the mainstream. In squatter settlements the situation is more critical. Sultanabad is one of the squatter settlements of Karachi. Purpose of case study is to improve the health of disabled children’s, and create awareness among the parents and community. Through a household visit, Shiraz, a young disabled boy of 15.5 years old was identified. Her mother articulated that her son was living normally and happily with his parents two years back. When he was 13 years old and student of class 8th, both his legs were traumatized in a Railway Train Accident while playing cricket. He got both femoral shaft fractured severely. He was taken to Jinnah Post Graduate Medical Centre (JPMC) where his left leg was amputated at above knee level and right leg was opened & fixed by reduction internally, luckily bone healed moderately with the passage of time. Methods: In Squatter settlements of Karachi Sultanabad, a survey was conducted in two sectors. Disability screening questionnaire was developed, collaboration with community through household visits, outreach sessions 23cases of disabled were identified who were socialized through sports, Musical program and get-together was organized with stockholder for creating awareness among community and parent’s. Collaboration was established with different NGOs, Government, stakeholders and community support for establishment of Physiotherapy Center. During home visit it was identified that Shiraz was on bed since last 1 year, his family could not afforded cost of physiotherapist and medical consultation due to poverty. Parents counseling was done mentioning that Shiraz needed to take treatment. After motivation his parents agreed for treatment. He was consulted by an orthopedic surgeon in AKUH, Who referred to DMC University of Health Science for rehabilitation service. There he was assessed and referred for Community Based Physiotherapy Centre Sultanabad. Physiotherapist visited home along with Coordinator for Special children and assessed him regularly, planned Physiotherapy treatment for abdominal, high muscles strutting exercise foot muscles strengthening exercise, knee mobilization weight bearing from partial to full weight gradually, also strengthen exercise were given for residual limb as the boy was dependent on it. He was also provided by an artificial leg and training was done. Result: Shiraz is now fully mobile, he can walk independently even out of home, functional ability progress improved and dependency factors reduced. It was difficult but not impossible. We all have sympathy but if we have empathy then we can rehabilitate the community in a better way. His parents are very happy and also the community is surprised to see him in such better condition. Conclusion: Combined efforts of physiotherapist, Coordinator of special children, community and parents made a drastic change in Shiraz’s case by continuously motivating him for better outcome. He is going to school regularly without support. Since he belongs to a poor family he faces financial constraints for education and clinical follow ups regularly.

Keywords: femoral shaft fracture, trauma, orthopedic surgeon, physiotherapy treatment

Procedia PDF Downloads 227