Search results for: innovative learning

Authors: Ambra Giovannelli, Coriolano Salvini

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Many efforts have been spent in the design and development of Concentrated Solar Power (CPS) Plants worldwide. Most of them are for on-grid electricity generation and they are large plants which can benefit from the economies of scale. Nevertheless, several potential applications for Small and Medium-Scale CSP plants can be relevant in the industrial sector as well as for off-grid purposes (i.e. in rural contexts). In a wide range of industrial processes, CSP technologies can be used for heat generation replacing conventional primary sources. For such market, proven technologies (usually hybrid solutions) already exist: more than 100 installations, especially in developing countries, are in operation and performance can be verified. On the other hand, concerning off-grid applications, solar technologies are not so mature. Even if the market offers a potential deployment of such systems, especially in countries where the access to grid is strongly limited, optimized solutions have not been developed yet. In this context, steam power plants can be taken into consideration for medium scale installations, due to the recent results achieved with direct steam generation systems based on paraboloidal dish or Fresnel lens solar concentrators. Steam at 4.0-4.5 MPa and 500°C can be produced directly by means of innovative solar receivers (some prototypes already exist). Although it could seem a promising technology, presently, steam turbines commercially available do not cover the required cycle specifications. In particular, while low-pressure turbines already exist on the market, high-pressure groups, necessary for the abovementioned applications, are not available. The present paper deals with the preliminary design of a high-pressure steam turbine group for a medium-scale CSP plant (200-1000 kWe). Such a group is arranged in a single geared package composed of four radial expander wheels. Such wheels have been chosen on the basis of automotive turbocharging technology and then modified to take the new requirements into account. Results related to the preliminary geometry selection and to the analysis of the high-pressure turbine group performance are reported and widely discussed.

Keywords: concentrated solar power (CSP) plants, steam turbine, radial turbine, medium-scale power plants

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Authors: Chonlakorn Wiboonsiriruk, Ekachai Phaisangittisagul, Chadchai Srisurangkul, Itsuo Kumazawa

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Public transportation is a crucial aspect of passenger transportation, with buses playing a vital role in the transportation service. Passenger counting is an essential tool for organizing and managing transportation services. However, manual counting is a tedious and time-consuming task, which is why computer vision algorithms are being utilized to make the process more efficient. In this study, different object detection algorithms combined with passenger tracking are investigated to compare passenger counting performance. The system employs the EfficientDet algorithm, which has demonstrated superior performance in terms of speed and accuracy. Our results show that the proposed system can accurately count passengers in varying conditions with an accuracy of 94%.

Keywords: computer vision, object detection, passenger counting, public transportation

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Authors: Hiromi Kawai

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This study investigates the nature of EFL older children’s L2 perceptive and productive abilities using classroom data, in order to find a pedagogical solution to the teaching of L2 sounds at an early stage of learning in a formal school setting. It is still inconclusive whether older children with only EFL formal school instruction at the initial stage of L2 learning are able to attain native-like perception and production in English within the very limited amount of exposure to the target language available. Based on the notion of the lack of study of EFL Japanese children’s acquisition of English segments, the researcher uses a model of L1 speech processing which was developed for investigating L1 English children’s speech and literacy difficulties using a psycholinguistic framework. The model is composed of input channel, output channel, and lexical representation, and examines how a child receives information from spoken or written language, remembers and stores it within the lexical representations and how the child selects and produces spoken or written words. Concerning language universality and language specificity in the language acquisitional process, the aim of finding any sound errors in L1 English children seemed to conform to the author’s intention to find abilities of English sounds in older Japanese children at the novice level of English in an EFL setting. 104 students in Grade 5 (between the ages of 10 and 11 years old) of an elementary school in Tokyo participated in this study. Four tests to measure their perceptive ability and three oral repetition tests to measure their productive ability were conducted with/without reference to lexical representation. All the test items were analyzed to calculate item facility (IF) indices, and correlational analyses and Structural Equation Modeling (SEM) were conducted to examine the relationship between the receptive ability and the productive ability. IF analysis showed that (1) the participants were better at perceiving a segment than producing a segment, (2) they had difficulty in auditory discrimination of paired consonants when one of them does not exist in the Japanese inventory, (3) they had difficulty in both perceiving and producing English vowels, and (4) their L1 loan word knowledge had an influence on their ability to perceive and produce L2 sounds. The result of the Multiple Regression Modeling showed that the two production tests could predict the participants’ auditory ability of real words in English. The result of SEM showed that the hypothesis that perceptive ability affects productive ability was supported. Based on these findings, the author discusses the possible explicit method of teaching English segments to EFL older children in a formal school setting.

Keywords: EFL older children, english segments, perception, production, speech processing system

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Authors: Linda Weinberg, Miriam Symon

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While few institutions of higher education in Israel offer international programs taught entirely in English, many Israeli students today can study at least one content course taught in English during their degree program. In particular, with the growth of international partnerships and opportunities for student mobility, English medium instruction is a growing phenomenon. There are however no official guidelines in Israel for how to develop and implement content courses in English and no training to help lecturers prepare for teaching their materials in a foreign language. Furthermore, the implications for the students and the nature of the courses themselves have not been sufficiently considered. In addition, the institution must have lecturers who are able to teach these courses effectively in English. An international project funded by the European Union addresses these issues and a set of guidelines which provide guidance for lecturers in adapting their courses for delivery in English have been developed. A train-the-trainer approach is adopted in order to cascade knowledge and experience in English medium instruction from experts to language teachers and on to content teachers thus maximizing the scope of professional development. To accompany training, a model English medium course has been created which serves the dual purpose of highlighting alternatives to the frontal lecture while integrating language learning objectives with content goals. This course can also be used as a standalone content course. The development of the guidelines and of the course utilized backwards, forwards and central design in an iterative process. The goals for combined language and content outcomes were identified first after which a suitable framework for achieving these goals was constructed. The assessment procedures evolved through collaboration between content and language specialists and subsequently were put into action during a piloting phase. Feedback from the piloting teachers and from the students highlight the need for clear channels of communication to encourage frank and honest discussion of expectations versus reality. While much of what goes on in the English medium classroom requires no better teaching skills than are required in any classroom, the understanding of students' abilities in achieving reasonable learning outcomes in a foreign language must be rationalized and accommodated within the course design. Concomitantly, preparatory language classes for students must be able to adapt to prepare students for specific language and cognitive skills and activities that courses conducted in English require. This paper presents findings from the implementation of a purpose-designed English medium instruction course arrived at through an iterative backwards, forwards and central design process utilizing feedback from students and lecturers alike leading to suggested guidelines for English medium instruction in higher education.

Keywords: English medium instruction, higher education, iterative design process, train-the-trainer

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Authors: Angelo Corallo, Maria Elena Latino, Marta Menegoli

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Agri-food value chain involves various stakeholders with different roles. All of them abide by national and international rules and leverage marketing strategies to advance their products. Food products and related processing phases carry with it a big mole of data that are often not used to inform final customer. Some data, if fittingly identified and used, can enhance the single company, and/or the all supply chain creates a math between marketing techniques and voluntary traceability strategies. Moreover, as of late, the world has seen buying-models’ modification: customer is careful on wellbeing and food quality. Food citizenship and food democracy was born, leveraging on transparency, sustainability and food information needs. Internet of Things (IoT) and Analytics, some of the innovative technologies of Industry 4.0, have a significant impact on market and will act as a main thrust towards a genuine ‘4.0 change’ for agriculture. But, realizing a traceability system is not simple because of the complexity of agri-food supply chain, a lot of actors involved, different business models, environmental variations impacting products and/or processes, and extraordinary climate changes. In order to give support to the company involved in a traceability path, starting from business model analysis and related business process a Framework to Manage Product Data in Agri-Food Supply Chain for Voluntary Traceability was conceived. Studying each process task and leveraging on modeling techniques lead to individuate information held by different actors during agri-food supply chain. IoT technologies for data collection and Analytics techniques for data processing supply information useful to increase the efficiency intra-company and competitiveness in the market. The whole information recovered can be shown through IT solutions and mobile application to made accessible to the company, the entire supply chain and the consumer with the view to guaranteeing transparency and quality.

Keywords: agriculture 4.0, agri-food suppy chain, industry 4.0, voluntary traceability

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Authors: S. Varnagiris, M. Urbonavicius, S. Tuckute, M. Lelis, K. Bockute

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Amongst many water purification techniques, TiO₂ photocatalysis is recognized as one of the most promising sustainable methods. It is known that for photocatalytical applications anatase is the most suitable TiO₂ phase, however heterojunction of anatase/rutile phases could improve the photocatalytical activity of TiO₂ even further. Despite the relative simplicity of TiO₂ different synthesis methods lead to the highly dispersed crystal phases and photocatalytic activity of the corresponding samples. Accordingly, suggestions and investigations of various innovative methods of TiO₂ synthesis are still needed. In this work structural and photocatalytical properties of TiO₂ films deposited by the unconventional method of simultaneous co-sputtering from two magnetrons powered by pulsed-Direct Current (pDC) and Radio Frequency (RF) power sources with negative bias voltage have been studied. More specifically, TiO₂ film thickness, microstructure, surface roughness, crystal structure, optical transmittance and photocatalytical properties were investigated by profilometer, scanning electron microscope, atomic force microscope, X-ray diffractometer and UV-Vis spectrophotometer respectively. The proposed unconventional two magnetron co-sputtering based TiO₂ film formation method showed very promising results for crystalline TiO₂ film formation while keeping process temperatures below 100 °C. XRD analysis revealed that by using proper combination of power source type and bias voltage various TiO₂ phases (amorphous, anatase, rutile or their mixture) can be synthesized selectively. Moreover, strong dependency between power source type and surface roughness, as well as between the bias voltage and band gap value of TiO₂ films was observed. Interestingly, TiO₂ films deposited by two magnetron co-sputtering without bias voltage had one of the highest band gap values between the investigated films but its photocatalytic activity was superior compared to all other samples. It is suggested that this is due to the dominating nanocrystalline anatase phase with various exposed surfaces including photocatalytically the most active {001}.

Keywords: films, magnetron co-sputtering, photocatalysis, TiO₂

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Authors: Khaled Mohammed

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This paper presents novel face recognition and identification approaches for the real-time attendance management problem in large companies/factories and government institutions. The proposed uses the Minimum Ratio (MR) approach for employee identification. Capturing the authentic face variability from a sequence of video frames has been considered for the recognition of faces and resulted in system robustness against the variability of facial features. Experimental results indicated an improvement in the performance of the proposed system compared to the Previous approaches at a rate between 2% to 5%. In addition, it decreased the time two times if compared with the Previous techniques, such as Extreme Learning Machine (ELM) & Multi-Scale Structural Similarity index (MS-SSIM). Finally, it achieved an accuracy of 99%.

Keywords: attendance management system, face detection and recognition, live face recognition, minimum ratio

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Authors: Garreth Kestell, Lukah Dykes, Danielle Zerk, Kyla Trewartha, Rhianon Marshall, Elena Rudnik

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Adolescent mental health is an international priority and the impact of innovative service models must be evaluated. Secondary school-based mental health services (SBMHS) involving private general practitioners and psychologists are a model of care being trialed in South Australia. Measures of depression, anxiety, and stress are routinely collected throughout psychotherapy sessions. This research set out to quantify the impact of psychotherapy for rural adolescents in a school setting and explore the importance of session frequency. Methods: Demographics, session date and DASS21 scores from students (n=65) seen in 2016 by three psychologists working at the SBMHS were recorded. Students were aged 13-18 years (M=15.43, SD= 1.24), mostly female (F=51, M=14), attended between 1 and 23 sessions with a median of 6 sessions (MAD 5.93) in one-year. The treating psychologist collected self-administered DASS21 scores. A mixed model analysis was used with age, sex, treating psychologist, months from first session, and session number as fixed effects, with response variables of DASS depression, anxiety, and stress scores. Results: 71.5% were classified as having extreme or severe anxiety and half had extreme or severe depression and/or stress scores. On average males had a greater increase in DASS scores over time but males attending more sessions benefited most from therapy. Discussion: Psychologists are treating rural adolescents in schools for severe anxiety, depression, and stress. This pilot study indicates that a predictive model combining demographics, session frequency, and DASS scores may help identify who is most likely to benefit from individual psychotherapy. Variations in DAS scores of individuals over time indicate the need for the collection of information such as living situation and exposure to alcohol. A larger sample size and additional data are currently being collected to allow for a more robust analysis.

Keywords: adolescent health, psychotherapy, school based mental health services, DAS21

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Authors: Julius Y Asamoah

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Mobile money has seen faster adoption in the decade. Its emergence serves as an essential driver of financial inclusion and an innovative financial service delivery channel, especially to the unbanked population. The rising importance of mobile money services has caught policymakers and regulators' attention, seeking to understand the many issues emerging from this context. At the same time, it is unlocking the potential of knowledge of this new technology. Regulatory responses and support are essential, requiring significant changes to current regulatory practices in Ghana. The article aims to answer the following research questions: "What risk does an unregulated mobile money service pose to consumers and the financial system? "What factors stimulate and hinder the introduction of mobile payments in developing countries? The sample size used was 250 respondents selected from the study area. The study has adopted an analytical approach comprising a combination of qualitative and quantitative data collection methods. Actor-network theory (ANT) is used as an interpretive lens to analyse this process. ANT helps analyse how actors form alliances and enrol other actors, including non-human actors (i.e. technology), to secure their interests. The study revealed that government regulatory policies impact mobile money as critical to mobile money services in developing countries. Regulatory environment should balance the needs of advancing access to finance with the financial system's stability and draw extensively from Kenya's work as the best strategies for the system's players. Thus, regulators need to address issues related to the enhancement of supportive regulatory frameworks. It recommended that the government involve various stakeholders, such as mobile phone operators. Moreover, the national regulatory authority creates a regulatory environment that promotes fair practices and competition to raise revenues to support a business-enabling environment's key pillars as infrastructure.

Keywords: actor-network theory (ANT), cashless future, Developing countries, Ghana, Mobile Money

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Authors: Michal Kozubík, Svetlana Síthová

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Aim: Aim of this study is to introduce the method of instrumental enrichment to people who works in the helping professions, and show further possibilities of its realization with children from socially disadvantaged backgrounds into society. Methods: We focused on Feuerstein’s Instrumental Enrichment method, its theoretical grounds and practical implementation. We carried out questionnaires and directly observed children from the disadvantaged background in Partizánske district. Results: We outlined the issues of children from disadvantaged social environment and their opportunity of social integration using the method. The findings showed the utility of Feuerstein method. Conclusions: We conclude that Feuerstein methods are very suitable for children from socially disadvantaged background and importance of social workers and special educator co-operation.

Keywords: Feuerstein, inclusion, education, socially disadvantaged background

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Authors: Rania A. Aboalela, Javed I. Khan

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This research presents a learning assessment theory of Cognitive Skill in Concept Space (CS2) to measure the assessed knowledge in terms of cognitive skill levels of the concepts. The cognitive skill levels refer to levels such as if a student has acquired the state at the level of understanding, or applying, or analyzing, etc. The theory is comprised of three constructions: Graph paradigm of a semantic/ ontological scheme, the concept states of the theory and the assessment analytics which is the process to estimate the sets of concept state at a certain skill level. Concept state means if a student has already learned, or is ready to learn, or is not ready to learn a certain skill level. The experiment is conducted to prove the validation of the theory CS2.

Keywords: cognitive skill levels, concept states, concept space, knowledge assessment theory

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Authors: Yu-Lin Chen, Kimberly Koester, Marissa Raymond-Flesh, Anika Thapar, Jay Thapar

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Purpose: Effectively communicating adolescent health topics to teens and their parents is crucial. This study emphasizes critically evaluating the optimal use of artificial intelligence tools (AI), which are increasingly prevalent in disseminating health information. By fostering a deeper understanding of AI voice preference in the context of health, the research aspires to have a ripple effect, enhancing the collective health literacy and decision-making capabilities of both teenagers and their parents. This study explores AI voices' potential within health learning modules for annual well-child visits. We aim to identify preferred voice characteristics and understand factors influencing perceived trustworthiness, ultimately aiming to improve health literacy and decision-making in both demographics. Methods: A cross-sectional study assessed preferences and trust perceptions of AI voices in learning modules among teens (11-18) and their parents/guardians in Northern California. The study involved the development of four distinct learning modules covering various adolescent health-related topics, including general communication, sexual and reproductive health communication, parental monitoring, and well-child check-ups. Participants were asked to evaluate eight AI voices across the modules, considering a set of six factors such as intelligibility, naturalness, prosody, social impression, trustworthiness, and overall appeal, using Likert scales ranging from 1 to 10 (the higher, the better). They were also asked to select their preferred choice of voice for each module. Descriptive statistics summarized participant demographics. Chi-square/t-tests explored differences in voice preferences between groups. Regression models identified factors impacting the perceived trustworthiness of the top-selected voice per module. Results: Data from 104 participants (teen=63; adult guardian = 41) were included in the analysis. The mean age is 14.9 for teens (54% male) and 41.9 for the parent/guardian (12% male). At the same time, similar voice quality ratings were observed across groups, and preferences varied by topic. For instance, in general communication, teens leaned towards young female voices, while parents preferred mature female tones. Interestingly, this trend reversed for parental monitoring, with teens favoring mature male voices and parents opting for mature female ones. Both groups, however, converged on mature female voices for sexual and reproductive health topics. Beyond preferences, the study delved into factors influencing perceived trustworthiness. Interestingly, social impression and sound appeal emerged as the most significant contributors across all modules, jointly explaining 71-75% of the variance in trustworthiness ratings. Conclusion: The study emphasizes the importance of catering AI voices to specific audiences and topics. Social impression and sound appeal emerged as critical factors influencing perceived trustworthiness across all modules. These findings highlight the need to tailor AI voices by age and the specific health information being delivered. Ensuring AI voices resonate with both teens and their parents can foster their engagement and trust, ultimately leading to improved health literacy and decision-making for both groups. Limitations and future research: This study lays the groundwork for understanding AI voice preferences for teenagers and their parents in healthcare settings. However, limitations exist. The sample represents a specific geographic location, and cultural variations might influence preferences. Additionally, the modules focused on topics related to well-child visits, and preferences might differ for more sensitive health topics. Future research should explore these limitations and investigate the long-term impact of AI voice on user engagement, health outcomes, and health behaviors.

Keywords: artificial intelligence, trustworthiness, voice, adolescent

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Authors: Priscilla Eng Lian Murphy

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This study examines the nature of student conceptions of mathematics in higher education using quantitative research methods. This study validates the Short Form of Conception of Mathematics survey as well as reveals the epistemological nature of student conceptions of mathematics. Using a random sample of mathematics students in Australia and New Zealand (N=274), this paper highlighted three key findings, of relevance to lecturers in higher education. Firstly, descriptive data shows that mathematics students in Australia and New Zealand reported that mathematics is about numbers and components, models and life. Secondly, models conceptions of mathematics predicted strong examination performances using regression analyses; and thirdly, there is a positive correlation between high mathematics examination scores and cohesive conceptions of mathematics.

Keywords: higher education, learning mathematics, mathematics performances, student conceptions of mathematics

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

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Authors: Ana Bilandzic, Marcus Foth, Greg Hearn

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In a narrow sense, innovation is the invention and commercialisation of a new product or service in the marketplace. The literature suggests places that support knowledge exchange and social interaction, e.g. coffee shops, to nurture innovative ideas. With the widespread success of Internet, interpersonal communication and interaction changed. Online platforms complement physical places for idea exchange and innovation – the rise of hybrid, ‘net localities.’ Further, since its introduction in 2003 by Chesbrough, the concept of open innovation received increased attention as a topic in academic research as well as an innovation strategy applied by companies. Open innovation allows companies to seek and release intellectual property and new ideas from outside of their own company. As a consequence, the innovation process is no longer only managed within the company, but it is pursued in a co-creation process with customers, suppliers, and other stakeholders. Quirky.com (Quirky), a company founded by Ben Kaufman in 2009, recognised the opportunity given by the Internet for knowledge exchange and open innovation. Quirky developed an online platform that makes innovation available to everyone. This paper reports on a study that analysed Quirky’s business process in an extended event-driven process chain (eEPC). The aim was to determine how the platform enabled crowdsourced innovation for physical products on the Internet. The analysis reveals that key elements of the business model are based on open innovation. Quirky is an example of how open innovation can support crowdsourced and crowdfunded product ideation, development and selling. The company opened up various stages in the innovation process to its members to contribute in the product development, e.g. product ideation, design, and market research. Throughout the process, members earn influence through participating in the product development. Based on the influence they receive, shares on the product’s turnover. The outcomes of the study’s analysis highlighted certain benefits of open innovation for product development. The paper concludes with recommendations for future research to look into opportunities of open innovation approaches to be adopted by tertiary institutions as a novel way to commercialise research intellectual property.

Keywords: business process, crowdsourced innovation, open innovation, Quirky

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Authors: Morgane Chatard, Clémentine Puech, Nathalie Perek, Frédéric Roche

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Several neurological disorders are linked to repeated hypoxia. The impact of such repeated hypoxic stress, on endothelial cells function of the blood-brain barrier (BBB) is little studied in the literature. Indeed, the study of hypoxic stress in cellular pathways is complex using hypoxia exposure because HIF 1α (factor induced by hypoxia) has a short half life. Our study presents an innovative induction method of repeated hypoxic stress, more reproducible, which allows us to study its impacts on an in vitro contact co-culture BBB model. Repeated hypoxic stress was induced by hydralazine (a mimetic agent of hypoxia pathway) during two hours and repeated during 24 hours. Then, BBB integrity was assessed by permeability measurements (transendothelial electrical resistance and membrane permeability), tight junction protein expressions (cell-ELISA and confocal microscopy) and by studying expression and activity of efflux transporters. First, this study showed that repeated hypoxic stress leads to a BBB’s dysfunction illustrated by a significant increase in permeability. This loss of membrane integrity was linked to a significant decrease of tight junctions’ protein expressions, facilitating a possible transfer of potential cytotoxic compounds in the brain. Secondly, we demonstrated that brain microvascular endothelial cells had set-up defence mechanism. These endothelial cells significantly increased the activity of their efflux transporters which was associated with a significant increase in their expression. In conclusion, repeated hypoxic stress lead to a loss of BBB integrity with a decrease of tight junction proteins. In contrast, endothelial cells increased the expression of their efflux transporters to fight against cytotoxic compounds brain crossing. Unfortunately, enhanced efflux activity could also lead to reducing pharmacological drugs delivering to the brain in such hypoxic conditions.

Keywords: BBB model, efflux transporters, repeated hypoxic stress, tigh junction proteins

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Authors: Ulrike Dowie, Ralph Grothmann

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Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

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Authors: Florin Leon

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This paper describes a simulator of traffic scenarios tailored to facilitate autonomous driving model training for urban environments. With the rising prominence of self-driving vehicles, the need for diverse datasets is very important. The proposed simulator provides a flexible framework that allows the generation of custom scenarios needed for the validation and enhancement of trajectory prediction algorithms. Its controlled yet dynamic environment addresses the challenges associated with real-world data acquisition and ensures adaptability to diverse driving scenarios. By providing an adaptable solution for scenario creation and algorithm testing, this tool proves to be a valuable resource for advancing autonomous driving technology that aims to ensure safe and efficient self-driving vehicles.

Keywords: autonomous driving, car simulator, machine learning, model training, urban simulation environment

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Authors: Marie-Claude Richard, Amelie Bolduc-Mokhtar, Mathieu Parent

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People who have experienced maltreatment in childhood subsequently face many parenting issues of their own, in particular when it comes to distancing themselves from the abusive behaviors they were exposed and had access to positive role models. Few studies have explored the factors explaining the ability to break the generational cycle of child maltreatment. However, deeper knowledge of the factors associated with intergenerational discontinuity could facilitate the development of innovative interventions and increase the preventive potential of existing programs. This poster presentation will be about a better understanding of the intergenerational transmission of maltreatment (IGTM) from the perspective of both youth protection workers and parents receiving child protection services. The data used to meet this goal were collected from a group interview with eight youth protection workers whose caseloads involved IGTM situations and through semi-structured interviews with four parents with a history of child protection services and who were currently receiving such services for at least one of their children. In the view of the youth protection workers, the IGTM refers to everything that is transmitted and not transmitted from one generation to the next within a family. The study participants painted quite a bleak portrait of the families affected by IGTM. However, three main avenues of intervention were mentioned by the participants: working within the network, favoring long-term interventions and being empathic. The results also show that the mothers were in a trajectory of intergenerational discontinuity in child maltreatment. Support from their families and friends as well as from formal support services brought out some possible explanatory factors for intergenerational discontinuity in child maltreatment. From a prevention perspective, developing meaningful and trusting relationships seems a source of resilience for parents who were placed in the care of the child protection system as children. The small number of participants limits the generalizability of these results. The difficulty of recruiting parents is a substantial challenge regarding gaining knowledge on the intergenerational transmission of child maltreatment. Future studies should examine this question and seek to develop effective strategies to help recruit study participants.

Keywords: child maltreatment, intergenerational transmission, prevention, qualitative data

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Authors: Vijaya

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This paper reports the results of a study that measures the level of receptive vocabularies using the Peabody Picture Vocabulary Test (PPVT) in an ESL context. PPVT is a popular standardized test used to measure the vocabulary level of L1 learners. In this study, PPVT was administered to fourteen 9 to 11 year old Indian ESL learners from the fifth standard from a school in Hyderabad. Their performance is compared with the age appropriate performance of L1 learners. Their performance on noun versus verb items is also compared. The results are discussed concerning the learning goals set by the National Council for Educational Research and Training (NCERT) position paper on Teaching of English in India.

Keywords: national council for educational research and training, India, PPVT, second language acquistion, vocabulary acquisition

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Authors: Riccardo Cacciotti, Jiri Frankl, Benjamin Wolf, Michael Machacek

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Moisture fluctuations govern the occurrence of fungi-related problems in buildings, which may impose significant health risks for users and even lead to structural failures. Several numerical engineering models attempt to capture the complexity of mold growth on building materials. From real life observations, in cases with suppressed daily variations of boundary conditions, e.g. in crawlspaces, mold growth model predictions well correspond with the observed mold growth. On the other hand, in cases with substantial diurnal variations of boundary conditions, e.g. in the ventilated cavity of a cold flat roof, mold growth predicted by the models is significantly overestimated. This study, founded by the Grant Agency of the Czech Republic (GAČR 20-12941S), aims at gaining a better understanding of mold growth behavior on solid wood, under varying boundary conditions. In particular, the experimental investigation focuses on the response of mold to changing conditions in the boundary layer and its influence on heat and moisture transfer across the surface. The main results include the design and construction at the facilities of ITAM (Prague, Czech Republic) of an innovative device allowing for the simulation of changing environmental conditions in buildings. It consists of a square section closed circuit with rough dimensions 200 × 180 cm and cross section roughly 30 × 30 cm. The circuit is thermally insulated and equipped with an electric fan to control air flow inside the tunnel, a heat and humidity exchange unit to control the internal RH and variations in temperature. Several measuring points, including an anemometer, temperature and humidity sensor, a loading cell in the test section for recording mass changes, are provided to monitor the variations of parameters during the experiments. The research is ongoing and it is expected to provide the final results of the experimental investigation at the end of 2022.

Keywords: moisture, mold growth, testing, wood

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Authors: Nada Farhani, Naim Terbeh, Mounir Zrigui

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The recognition of the objects contained in images has always presented a challenge in the field of research because of several difficulties that the researcher can envisage because of the variability of shape, position, contrast of objects, etc. In this paper, we will be interested in the recognition of objects. The classical Hough Transform (HT) presented a tool for detecting straight line segments in images. The technique of HT has been generalized (GHT) for the detection of arbitrary forms. With GHT, the forms sought are not necessarily defined analytically but rather by a particular silhouette. For more precision, we proposed to combine the results from the GHT with the results from a calculation of similarity between the histograms and the spatiograms of the images. The main purpose of our work is to use the concepts from recognition to generate sentences in Arabic that summarize the content of the image.

Keywords: recognition of shape, generalized hough transformation, histogram, spatiogram, learning

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Authors: Mohammed Agbali, Claudia Trillo, Yusuf Arayici, Terrence Fernando

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The wide-spread adoption of the Smart City concept has introduced a new era of computing paradigm with opportunities for city administrators and stakeholders in various sectors to re-think the concept of urbanization and development of healthy cities. With the world population rapidly becoming urban-centric especially amongst the emerging economies, social innovation will assist greatly in deploying emerging technologies to address the development challenges in core sectors of the future cities. In this context, sustainable health-care delivery and improved quality of life of the people is considered at the heart of the healthy city agenda. This paper examines the Boston innovation landscape from the perspective of smart services and innovation ecosystem for sustainable development, especially in transportation and healthcare. It investigates the policy implementation process of the Healthy City agenda and eHealth economy innovation based on the experience of Massachusetts’s City of Boston initiatives. For this purpose, three emerging areas are emphasized, namely the eHealth concept, the innovation hubs, and the emerging technologies that drive innovation. This was carried out through empirical analysis on results of public sector and industry-wide interviews/survey about Boston’s current initiatives and the enabling environment. The paper highlights few potential research directions for service integration and social innovation for deploying emerging technologies in the healthy city agenda. The study therefore suggests the need to prioritize social innovation as an overarching strategy to build sustainable Smart Cities in order to avoid technology lock-in. Finally, it concludes that the Boston example of innovation economy is unique in view of the existing platforms for innovation and proper understanding of its dynamics, which is imperative in building smart and healthy cities where quality of life of the citizenry can be improved.

Keywords: computing paradigm, emerging technologies, equitable healthcare, healthy cities, open data, smart city, social innovation

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Authors: Thiru Vandeyar

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The present study set out to determine how Q methodology may be used as an inclusive education policy development process. Utilising Q-methodology as a strategy of inquiry, this qualitative instrumental case study set out to explore how teachers, as a crucial but often neglected human resource, may be included in developing policy. A social constructivist lens and the theoretical moorings of Proudford’s emancipatory approach to educational change anchored in teachers’ ‘writerly’ interpretation of policy text was employed. Findings suggest that Q-method is a unique research approach to include teachers’ voices in policy development. Second, that beliefs, attitudes, and professionalism of teachers to improve teaching and learning using ICT are integral to policy formulation. The study indicates that teachers have unique beliefs about what statements should constitute a school’s information and communication (ICT) policy. Teachers’ experiences are an extremely valuable resource in and should not be ignored in the policy formulation process.

Keywords: teachers, q-methodology, education policy, ICT

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Authors: Muhammad Yayat Afianto, Darmawan, Agung Putra Utama, Hari Kushardanto

Abstract:

Fish Forever, Rare’s innovative coastal fisheries program, combined community-based conservation management approach with spatial management to restore and protect Indonesia’s small-scale fisheries by establishing Fishing Managed Access Area. A ‘TURF-Reserve’ is a fishery management approach that positions fishers at the center of fisheries management, empowering them to take care of and make decisions about the future of their fishery. After two years of the program, social marketing campaigns succeeded in changing their behavior by adopting the new conservation behavior. The Pride-TURF-R campaigns developed an overarching hypothesis of impact that captured the knowledge, attitude and behavior changes needed to reduce threats and achieve conservation results. Rare help Batu Belah fishers to develop their group, developed with their roles, sustainable fisheries plan, and the budget plan. On 12th February 2017, the Head of Loka Kawasan Konservasi Perairan Nasional (LKKPN) which is a Technical Implementation Unit for National Marine Conservation Areas directly responsible to the Directorate General for Marine Spatial Management in the Ministry of Marine Affairs and Fisheries had signed a Partnership Agreement with the Head of Batu Belah Village to manage a TURF+Reserve area as wide as 909 hectares. The fishers group have been collecting the catch and submitting the report monthly, initiated the installation of the buoy markers for the No Take Zone, and formed the Pokmaswas (community-based surveillance group). Prior to this behavior adoption, they don’t have any fisheries data, no group of fishers, and they have still fishing inside the No Take Zone. This is really a new behavior adoption for them. This paper will show the process and success story of the social marketing campaign to conserve marine habitat in Anambas through Pride-TURF-R program.

Keywords: behavior adoption, community participation, no take zone, pride-TURF-R

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Authors: Halimat M. Ajose-Adeogun, Zaynab A. Bello

Abstract:

Artificial Intelligence (AI) and Natural Language Processing (NLP) have transformed computer language comprehension, allowing computers to comprehend spoken and written language with human-like cognition. NLP, a multidisciplinary area that combines rule-based linguistics, machine learning, and deep learning, enables computers to analyze and comprehend human language. NLP applications in medicine range from tackling issues in electronic health records (EHR) and psychiatry to improving diagnostic precision in orthopedic surgery and optimizing clinical procedures with novel technologies like chatbots. The technology shows promise in a variety of medical sectors, including quicker access to medical records, faster decision-making for healthcare personnel, diagnosing dysplasia in Barrett's esophagus, boosting radiology report quality, and so on. However, successful adoption requires training for healthcare workers, fostering a deep understanding of NLP components, and highlighting the significance of validation before actual application. Despite prevailing challenges, continuous multidisciplinary research and collaboration are critical for overcoming restrictions and paving the way for the revolutionary integration of NLP into medical practice. This integration has the potential to improve patient care, research outcomes, and administrative efficiency. The research methodology includes using NLP techniques for Sentiment Analysis and Emotion Recognition, such as evaluating text or audio data to determine the sentiment and emotional nuances communicated by users, which is essential for designing a responsive and sympathetic chatbot. Furthermore, the project includes the adoption of a Personalized Intervention strategy, in which chatbots are designed to personalize responses by merging NLP algorithms with specific user profiles, treatment history, and emotional states. The synergy between NLP and personalized medicine principles is critical for tailoring chatbot interactions to each user's demands and conditions, hence increasing the efficacy of mental health care. A detailed survey corroborated this synergy, revealing a remarkable 20% increase in patient satisfaction levels and a 30% reduction in workloads for healthcare practitioners. The poll, which focused on health outcomes and was administered to both patients and healthcare professionals, highlights the improved efficiency and favorable influence on the broader healthcare ecosystem.

Keywords: natural language processing, artificial intelligence, healthcare communication, electronic health records, patient care

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Authors: Aya M. H. Eissa, Ayman H. A. Mahmoud

Abstract:

When it comes to energy efficient thermal regulation system, natural systems do not only offer an inspirational source of innovative strategies but also sustainable and even regenerative ones. Using biomimetic design an energy efficient thermal regulation system can be developed. Although, conventional design process methods achieved fairly efficient systems, they still had limitations which can be overcome by using parametric design software. Accordingly, the main objective of this study is to apply and assess the efficiency of heat regulation strategies inspired from termite mounds in residential buildings’ thermal regulation system. Parametric design software is used to pave the way for further and more complex biomimetic design studies and implementations. A hot arid region is selected due to the deficiency of research in this climatic region. First, the analysis phase in which the stimuli, affecting, and the parameters, to be optimized, are set mimicking the natural system. Then, based on climatic data and using parametric design software Grasshopper, building form and openings height and areas are altered till settling on an optimized solution. Finally, an assessment of the efficiency of the optimized system, in comparison with a conventional system, is determined by firstly, indoors airflow and indoors temperature, by Ansys Fluent (CFD) simulation. Secondly by and total solar radiation falling on the building envelope, which was calculated using Ladybug, Grasshopper plugin. The results show an increase in the average indoor airflow speed from 0.5m/s to 1.5 m/s. Also, a slight decrease in temperature was noticed. And finally, the total radiation was decreased by 4%. In conclusion, despite the fact that applying a single bio-inspired heat regulation strategy might not be enough to achieve an optimum system, the concluded system is more energy efficient than the conventional ones as it aids achieving indoors comfort through passive techniques. Thus demonstrating the potential of parametric design software in biomimetic design.

Keywords: biomimicry, heat regulation systems, hot arid regions, parametric design, thermal comfort

Procedia PDF Downloads 285

Authors: Frazer G. Thompson

Abstract:

Israel is a nation of cultural and historical diversity, yet the success factors for a modern Bedouin-Arab high-tech entrepreneur seem to be different from those of other Jewish-Israeli citizens. The purpose of this descriptive narrative case study is to explore how an Arab-Israeli all Negev-Bedouin technology company has succeeded in the Israeli high-tech industry by utilizing technology and engineering career opportunities available to Bedouin youth for ‘Sadel Tech,’ at Be’er-Sheva, the Negev, Israel. Methods: The strategy of inquiry seeks to explore real-life contextual understandings, multi-level perspectives, and the cultural influences of personal, community, educational, and entrepreneurial factors. The research methodology includes in-depth one-on-one interviews, focus group sessions, and overt observation to explore the meaning and understanding of the constructs toward determining the effect all or a few of the elements may have on the overall success factors of the company. Results: Study results indicate that the state-run educational system in Israel fails to adequately integrate important aspects of Bedouin culture into the learning environment. However, Bedouin entrepreneurs are finding ways to compensate for these inadequacies by utilizing non-traditional methods of teaching, learning, and doing business. Government incentives for Bedouin start-ups are also recognized as contributors. Employees of Sadel live and work in the Negev, the Gaza Strip, and the West Bank, further informing the study that the traditions of tribal etiquette continue to contribute to modern Bedouin-Arab business culture. Conclusion: Bedouin's business success in Israel is a multi-dimensional concept. While cultural acumen plays a prominent and unique role for both Arab-Israelis and Jewish-Israelis in economic and entrepreneurial pursuits, the marginalization of the Bedouin continues to contribute to the lack of educational and professional opportunities for Bedouin in Israel. Although recognized as important at the government level, programs necessary to implement the infrastructure required to support Bedouin entrepreneurship in Israel remain infantile. The Israeli Government is providing opportunities through grants and other incentives for Bedouin entrepreneurial start-ups, indicating that Israel has recognized the impact of this growing demographic. However, although many Bedouin graduates from University each year with advanced degrees, opportunities for Bedouin within the Israeli high-tech sector remain scarce.

Keywords: Bedouin education, Bedouin entrepreneur, economic anthropology, ethnic business opportunities, Israeli tech, Silicon Wadi

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Authors: Nikhil Byanna, Abdolghani Ebrahimi, Diego Klabjan

Abstract:

How does one objectively measure the performance of an individual offensive lineman in the NFL? The existing literature proposes various measures that rely on subjective assessments of game film, but has yet to develop an objective methodology to evaluate performance. Using a variety of statistics related to an offensive lineman’s performance, we develop a framework to objectively analyze the overall performance of an individual offensive lineman and determine specific linemen who are overvalued or undervalued relative to their salary. We identify eight players across the 2013-2014 and 2014-2015 NFL seasons that are considered to be overvalued or undervalued and corroborate the results with existing metrics that are based on subjective evaluation. To the best of our knowledge, the techniques set forth in this work have not been utilized in previous works to evaluate the performance of NFL players at any position, including offensive linemen.

Keywords: offensive lineman, player performance, NFL, machine learning

Procedia PDF Downloads 139

Authors: Omer Salih Dawood Omer, Safa Eltayeb, Imtithal A. Saeed

Abstract:

This research aimed to provide a convenient and secure web-based environment for students to practice Structured Query Language (SQL) through online assignments, enabling them to enhance their performance with immediate feedback from an automatically evaluating system. Additionally, the system allows students to take exams online with automatic performance evaluation. Our methodology consists of four phases: firstly,execution and comparison of student answers with model answers; secondly, direct comparison without execution which is useful for database-altering queries; thirdly, matching student answers with historically evaluated answers; and finally, manual evaluation by the teacher if prior phases fail. Applied practically, the methodology achieved excellent

Keywords: SQL assessment, online assessment, e-learning, e-exams

Procedia PDF Downloads 12