Search results for: academic learning integration

Authors: Dalila Lino

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The power of play for learning and development in early childhood education is beyond question. The main goal of this study is to analyse how three contemporary early childhood pedagogical approaches, the High Scope, the Modern School Movement (MEM) and the Pedagogy of Participation integrate play in their curriculum development. From this main goal the following objectives emerged: (i) to characterize how play is integrated in the daily routine of the pedagogical approaches under study; (ii) to analyse the teachers’ role during children’s playing situations; (iii) to identify the types of play that children are more often involved. The methodology used is the qualitative approach and is situated under the interpretative paradigm. Data is collected through semi-structured interviews to 30 preschool teachers and through observations of typical daily routines. The participants are 30 Portuguese preschool classrooms attending children from 3 to 6 years and working with the High Scope curriculum (10 classrooms), the MEM (10 classrooms) and the Pedagogy of Participation (10 classrooms). The qualitative method of content analysis was used to analyse the data. To ensure confidentiality, no information is disclosed without participants' consent, and the interviews were transcribed and sent to the participants for a final revision. The results show that there are differences how play is integrated and promoted in the three pedagogical approaches. The teachers’ role when children are at play varies according the pedagogical approach adopted, and also according to the teachers’ understanding about the meaning of play. The study highlights the key role that early childhood curriculum models have to promote opportunities for children to play, and therefore to be involved in meaningful learning.

Keywords: curriculum models, early childhood education, pedagogy, play

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Authors: E. Fredrick Rice

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Over the past three decades, a substantial body of academic literature has asserted that the pressure to maintain household income can negatively affect the personal well-being of breadwinners. Given that scholars have failed to thoroughly explore this phenomenon with breadwinners who are also business owners, theory has been underdeveloped in the entrepreneurial context. To identify the most appropriate theories to apply to entrepreneurs, the current paper utilized two approaches. First, a comprehensive bibliographic analysis was conducted focusing on works at the intersection of breadwinner status and well-being. Co-authorship and journal citation patterns highlighted relative resource theory as a boundary spanning approach with promising applications in the entrepreneurial space. To build upon this theory, regression analysis was performed using data from the Panel Study of Entrepreneurial Dynamics (PSED). Empirical results showed evidence for the effects of breadwinner status and household income on entrepreneurial well-being. Further, the findings suggest that it is not merely income or job status that predicts well-being, but one’s relative financial contribution compared to that of one’s non-breadwinning organizationally employed partner. This paper offers insight into how breadwinner status can be studied in relation to the entrepreneurial personality.

Keywords: breadwinner, entrepreneurship, household income, well-being.

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Authors: Philip Speranza

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As everyday transit options are shifting from autocentric to pedestrian and bicycle oriented modes for healthy living, downtown streets are becoming more attractive places to live. However, tools and methods to measure the natural environment at the small scale of streets do not exist. Fortunately, a combination of mobile data collection technology and parametric urban design software now allows an interface to relate urban ecological conditions. This paper describes creation of an interactive tool to measure urban phenomena of air, water, and heat/light at the scale of new three-by-three block pedestrianized areas in Barcelona called Superilles. Each Superilla limits transit to the exterior of the blocks and to create more walkable and bikeable interior streets for healthy living. The research will describe the integration of data collection, analysis, and design output via a live interface using parametric software Rhino Grasshopper and the Human User Interface (UI) plugin.

Keywords: transit, urban design, GIS, parametric design, Superilles, Barcelona, urban ecology

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Authors: Shijie Liu, Jehnming Lin

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This study mainly discussed the mechanical properties of selective laser sintered 304L stainless steel powder specimen. According to a single layer specimen sintering, the microstructure and porosity were observed to find out the proper sintering parameters. A multi-layer sintering experiment was conducted. Based on the microstructure and the integration between layers, the suitable parameters were found out. Finally, the sintered specimens were examined by metallographical inspection, hardness test, tensile test, and surface morphology measurement. The structure of the molten powder coated with unmelted powder was found in metallographic test. The hardness of the sintered stainless steel powder is greater than the raw material. The tensile strength is less than the raw material, and it is corresponding to different scanning paths. The specimen will have different patterns of cracking. It was found that the helical scanning path specimen will have a warpage deformation at the edge of the specimen. The S-scan path specimen surface is relatively flat.

Keywords: laser sintering, sintering path, microstructure, mechanical properties

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Authors: N. Drir, L. Barazane, M. Loudini

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It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.

Keywords: maximum power point tracking, neural networks, photovoltaic, P&O

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Authors: Xiao Yihong, Yu Kexin, Burra Venkata Durga Kumar

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With the accelerating process of urbanization, the problem of urban road congestion is becoming more and more serious. Intelligent transportation system combining distributed and artificial intelligence has become a research hotspot. As the core development direction of the intelligent transportation system, Cooperative Intelligent Transportation System (C-ITS) integrates advanced information technology and communication methods and realizes the integration of humans, vehicle, roadside infrastructure, and other elements through the multi-agent distributed system. By analyzing the system architecture and technical characteristics of C-ITS, the report proposes a distributed multi-agent C-ITS. The system consists of Roadside Sub-system, Vehicle Sub-system, and Personal Sub-system. At the same time, we explore the scalability of the C-ITS and put forward incorporating local rewards in the centralized training decentralized execution paradigm, hoping to add a scalable value decomposition method. In addition, we also suggest introducing blockchain to improve the safety of the traffic information transmission process. The system is expected to improve vehicle capacity and traffic safety.

Keywords: distributed system, artificial intelligence, multi-agent, cooperative intelligent transportation system

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Authors: David Julian Bernal Melgarejo

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Inland Waterway Transportation (IWT) is playing an important role in national transport systems, water transportation is considered to be safe, energy efficient and environmentally friendly mode of transport, considering all the benefits of IWT the Colombian government is planning to restore the Magdalena’s River navigability, embrace waterway transportation in Colombia could strength competitiveness while reduce most of the transport externalities. However, the current situation of the Magdalena deplorable, the most important river of Colombia has been abandoned for decades and the solution is beyond of a single administrative entity. This paper analyzes the outcomes of the Navigation And Inland Waterway Action and Development in Europe (NAIADES) program as a prospective to develop a sustainable program in Colombia. In order to guarantee the long-term future, and the adaptability of the program a research based on individual interviews with stakeholders and policy experts were carried out, findings support the idea of lack of integration within governmental institution, develop marketing strategies and human resources.

Keywords: inland waterway transportation, logistics, sustainability, multimodal transport systems, water transportation

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Authors: B. G. Abiona

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This study compared profitability analysis of integrated and non-integrated fish farming in Ogun State, Nigeria. Primary data were collected using interview guide. Random sampling techniques was used to select 133 non-integrated fish farmers (NIFF) and 216 integrated fish farmers (IFF) (n = 349) from the study area. Data were analyzed using Chi-square, T-test and Pearson Product moment correlation. Results showed that 92.5% of NIFF was male compared to IFF (90.7%). Also, 96.8% of IFF and 79.7% of NIFF were married. The mean ages of sampled farmers were 44 years (NIFF) and 46 years (IFF) while the mean fish farming experiences were 4 years (NIFF) and 5 years (IFF). Also, the average net profit per year of integrated fish farmers was ₦162,550 compared to NIFF (₦61,638). The chi-square analyses showed that knowledge of fish farming had significant relationship with respondents sex (χ2 = 9.44, df = 2, p < 0.05), age (r = 0.20, p< 0.05) and farming experience (r = p = 0.05). Significant differences exist between integrated and non-integrated fish farming, considering their knowledge of fish farming (t = 21.5, χ = 43.01, p < 0.05). The study concluded that IFF are more profitable compared to NIFF. It was recommended that private investors and NGOs should sponsor short training and courses which will enhance efficiency of fish farming to boost productivity among fish farmers.

Keywords: profitability analysis, farms, integration

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Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

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Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

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Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

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The swift proliferation of telehealth Internet of Things (IoT) devices has sparked concerns regarding energy consumption and the need for streamlined data processing. This paper presents an energy-efficient model that integrates telehealth IoT devices into a platform based on fog and cloud computing. This integrated system provides a sustainable and robust solution to address the challenges. Our model strategically utilizes fog computing as a localized data processing layer and leverages cloud computing for resource-intensive tasks, resulting in a significant reduction in overall energy consumption. The incorporation of adaptive energy-saving strategies further enhances the efficiency of our approach. Simulation analysis validates the effectiveness of our model in improving energy efficiency for telehealth IoT systems, particularly when integrated with localized fog nodes and both private and public cloud infrastructures. Subsequent research endeavors will concentrate on refining the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability across various healthcare and industry sectors.

Keywords: energy-efficient, fog computing, IoT, telehealth

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Authors: Moet Moet Myint Lay

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Continuing professional development involves acquiring new knowledge and skills for current work and improving career opportunities in the field through continuing education (OECD, 2000). This article examines the effectiveness of CPD in improving teacher quality and the resulting need for CPD for teacher educators in Myanmar. The purpose of this study is to explore a deeper understanding of teacher-to-teacher continuing professional development in improving teacher education programs. Research questions: (1) How do teachers in Myanmar understand the idea of continuous professional development for professional development? (2) What CPD activities are required for all teachers in teachers' colleges? (3) What are the main challenges of CPD implementation in Myanmar Education College? A qualitative method using semi-structured interviews was used in this study. Seven teacher educators from Mandalay Education College participated in this study. There are three male teacher educators and four female teacher educators. All participants who responded to the semi-structured interviews were between 29 and 45 years old.The interviews revealed that professional development involves acquiring the necessary pedagogical knowledge and skills to encourage students to think creatively and critically. Teachers must participate in a variety of activities, including professional interviews, lesson study, training programs, workshops, and seminars. All results showed that teachers need English and ICT skills for teaching and learning, including extended ICT courses for those who have completed a foundation course, access to e-libraries, and inclusive education (including language teaching and learning), facilitate the assessment (formative and summative), practicum, mentoring, and coaching skills. The study concludes with practical findings that suggest an urgent need for CPD activities for teachers.

Keywords: continuous professional development, teacher educator, teacher training program), mentoring

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Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

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Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

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Authors: Diane M. Bender

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In design education, professional education is delivered in a studio, where students learn and understand their discipline. This learning methodology culminates in a final review, where students present their work before instructors and invited reviewers, known as jurors. These jurors are recognized experts who add a wide diversity of opinions in their feedback to students. This feedback can be provided in multiple formats, mainly a verbal critique of the work. To better understand how these expert reviewers prepare for a studio review, a survey was distributed to reviewers at a multi-disciplinary design school within the United States. Five design disciplines are involved in this case study: architecture, graphic design, industrial design, interior design, and landscape architecture. Respondents (n=122) provided information about if and how they received training on how to critique and participate in a final review. Common forms of training included mentorship, modeled behavior from other designers/past professors, workshops on critique from the instructing faculty prior to the crit session, and by being a practicing design professional. Respondents also gave feedback about how much the instructor provided course materials prior to the review in order to better prepare for student interaction. Finally, respondents indicated if they had interaction, and in what format, with students prior to the final review. Typical responses included participation in studio desk crits, a midterm jury member, meetings with students, and email or social media correspondence. While the focus of this study is the studio review, the findings are equally applicable to other disciplines. Suggestions will be provided on how to improve the preparation of guests in the learning process and how their interaction can positively influence student engagement.

Keywords: critique, design, education, evaluation, juror

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Authors: Hen Friman

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Various categories of aqueous solutions are discharged within residential, institutional, commercial, and industrial structures. To safeguard public health and preserve the environment, it is imperative to subject wastewater to treatment processes that eliminate pathogens (such as bacteria and viruses), nutrients (such as nitrogen and phosphorus), and other compounds. Failure to address untreated sewage accumulation can result in an array of adverse consequences. Israel exemplifies a special case in wastewater management. Appropriate wastewater treatment significantly benefits sectors such as agriculture, tourism, horticulture, and industry. Nevertheless, untreated sewage in settlements lacking proper sewage collection or transportation networks remains an ongoing and substantial threat. Notably, the process of wastewater treatment entails substantial energy consumption. Consequently, this study explores the integration of solar energy as a renewable power source within the wastewater treatment framework. By incorporating renewable energy sources into the process, costs can be minimized, and decentralized facilities can be established even in areas lacking adequate infrastructure for traditional treatment methods.

Keywords: renewable energy, solar energy, innovative, wastewater treatment

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Authors: Ahteshamul Haq, Srikant Gupta, Murshid Kamal, Irfan Ali

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This case study designs and builds a multi-objective production planning model for a hardware firm with certain & uncertain data. During the time of interaction with the manager of the firm, they indicate some of the parameters may be vague. This vagueness in the formulated model is handled by the concept of fuzzy set theory. Triangular & Trapezoidal fuzzy numbers are used to represent the uncertainty in the collected data. The fuzzy nature is de-fuzzified into the crisp form using well-known defuzzification method via graded mean integration representation method. The proposed model attempts to maximize the production of the firm, profit related to the manufactured items & minimize the carrying inventory costs in both certain & uncertain environment. The recommended optimal plan is determined via fuzzy programming approach, and the formulated models are solved by using optimizing software LINGO 16.0 for getting the optimal production plan. The proposed model yields an efficient compromise solution with the overall satisfaction of decision maker.

Keywords: production planning problem, multi-objective optimization, fuzzy programming, fuzzy sets

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Authors: Aysegul Evren Yapicioglu

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The social roles and responsibilities expected from citizens are increasing due to changing global living conditions. Science education is expected to prepare conscious and sensitive students. Because today’s students are the adults of future. Precondition of this task is Teacher Education. In the past decade, one of the most important research field is socioscientific issues. This study deals with advantages and disadvantages of socioscientific issue based instruction in science classroom according to pre-service science teachers’ views. A case study approach that is one of the qualitative research design was used to explore their views. Fourteen pre-service science teachers participated to instruction process. Dolphinariums, Kyoto Protocol, genetically modified organisms, recyclable black bags’ benefits and damages, genetic tests, alternative energy sources and organ donation are examples of socioscientific issues, which were taught through activities in a special teaching course. Diaries and focus group interview were used as data collection tools. As a result of the study, the advantages of socioscientific issue based instruction in science classroom comprise of six sub-categories which are multi-skilling, social awareness development of thinking, meaningful learning, character and professional development, contribution of scientific literacy whereas disadvantages of this instruction process are challenges teachers and students, limitations of teaching and learning process in pre-service science teachers’ perspectives. Finally, this study contributes to science teachers and researchers to overcome disadvantages and benefit from the advantage of socioscientific issue based instruction in science classroom.

Keywords: science education, socioscientific issues, socioscientific issue based instruction, pre-service science teacher

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Authors: Diana Santiago, Tania Lisboa, Sophie Lee, Alexander P. Demos, Monica C. S. Vasconcelos

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Memorization has long been recognized as an arduous and anxiety-evoking task for musicians, and yet, it is an essential aspect of performance. Research shows that musicians are often not taught how to memorize. While memorization and practice strategies of professionals have been studied, little research has been done to examine how student musicians learn to practice and memorize music in different cultural settings. We present the process of developing and testing a questionnaire of music memorization and musical practice for student musicians in the UK and Brazil. A survey was developed for a cross-cultural research project aiming at examining how young orchestral musicians (aged 7–18 years) in different learning environments and cultures engage in instrumental practice and memorization. The questionnaire development included members of a UK/US/Brazil research team of music educators and performance science researchers. A pool of items was developed for each aspect of practice and memorization identified, based on literature, personal experiences, and adapted from existing questionnaires. Item development took the varying levels of cognitive and social development of the target populations into consideration. It also considered the diverse target learning environments. Items were initially grouped in accordance with a single underlying construct/behavior. The questionnaire comprised three sections: a demographics section, a section on practice (containing 29 items), and a section on memorization (containing 40 items). Next, the response process was considered and a 5-point Likert scale ranging from ‘always’ to ‘never’ with a verbal label and an image assigned to each response option was selected, following effective questionnaire design for children and youths. Finally, a pilot study was conducted with young orchestral musicians from diverse learning environments in Brazil and the United Kingdom. Data collection took place in either one-to-one or group settings to facilitate the participants. Cognitive interviews were utilized to establish response process validity by confirming the readability and accurate comprehension of the questionnaire items or highlighting the need for item revision. Internal reliability was investigated by measuring the consistency of the item groups using the statistical test Cronbach’s alpha. The pilot study successfully relied on the questionnaire to generate data about the engagement of young musicians of different levels and instruments, across different learning and cultural environments, in instrumental practice and memorization. Interaction analysis of the cognitive interviews undertaken with these participants, however, exposed the fact that certain items, and the response scale, could be interpreted in multiple ways. The questionnaire text was, therefore, revised accordingly. The low Cronbach’s Alpha scores of many item groups indicated another issue with the original questionnaire: its low level of internal reliability. Several reasons for each poor reliability can be suggested, including the issues with item interpretation revealed through interaction analysis of the cognitive interviews, the small number of participants (34), and the elusive nature of the construct in question. The revised questionnaire measures 78 specific behaviors or opinions. It can be seen to provide an efficient means of gathering information about the engagement of young musicians in practice and memorization on a large scale.

Keywords: cross-cultural, memorization, practice, questionnaire, young musicians

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Authors: Marilei Amadeu Sabino

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Idiomatic expressions are linguistic phraseologisms present in natural languages. Known to be metaphorical linguistic combinations, a good majority of them provide elements that reveal important cultural aspects of their linguistic community through their metaphors. With the advent of Cognitive Linguistics (more specifically of Cognitive Semantics), the metaphor ceased to be related to poetic language and rhetorical embellishment and came to be seen as part of simple everyday language, reflecting the way human beings think, act and conceive reality, i. e., a fundamental mechanism of human conceptualizations of the world. In this sense, it came to be conceived as an inevitable mechanism for representing the nature of thought and language. The speakers, in conceptualizing reality, often use metaphorically parts of the body in expressions known as somatic. Several conceptual metaphors appear to be potentially universal or near-universal, because people across the world share certain bodily experiences. In these terms, many linguistic metaphors may be identical or very similar in several languages. These similarities, according to the Theory of Conceptual Metaphor, derive from universal aspects of the human body. Thus, this research aims to investigate the nature of some metaphors underlying somatic idiomatic expressions of Portuguese, Italian and English languages, establishing a pattern of similarities and differences among them from a trilingual perspective. The analysis shows that much of the studied expressions are really structurally, semantically and metaphorically identical or similar in the three languages. These findings incite relevant discussions concerning mother and foreign language learning and aim to contribute to the teaching of phraseological Lexicon as well as to materials development in mono and multilingual perspectives.

Keywords: idiomatic expressions, materials development, metaphors, phraseological lexicon, teaching and learning

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Authors: Hafez Abdo, Rob Ackrill

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Renewable energy (RE) promotion in the UK relies on multiple policy instruments, which are required to overcome the path dependency pressures favouring fossil fuels. These instruments include targeted funding schemes and economy-wide instruments embedded in the tax code. The resulting complexity of incentives raises important questions around the coherence and effectiveness of these instruments for RE generation. This complexity is exacerbated by UK RE policy being nested within EU policy in a multi-level governance (MLG) setting. To gain analytical traction on such complexity, this study will analyse policies promoting the on-farm generation of energy for heat and power, from farm and food waste, via anaerobic digestion. Utilising both primary and secondary data, it seeks to address a particular lacuna in the academic literature. Via a localised, in-depth investigation into the complexity of policy instruments promoting RE, this study will help our theoretical understanding of the challenges that MLG and path dependency pressures present to policymakers of multi-dimensional policies.

Keywords: anaerobic digestion, energy, green, policy, renewable, tax, UK

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Authors: Geoffrey Sinha

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Today’s students are connected to the digital generation and technology is an integral part of their everyday lives. Clearly, this is one social revolution that is here to stay and the language classroom has been no exception. Furthermore, today’s teachers are also expected to connect with technology and online tools in their curriculum. However, it’s often difficult for teachers to know where to start, what resources and tools are available, what students should use, and most importantly, how to effectively use them in the classroom.

Keywords: language learning, new media, social media, technology

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Authors: Bruno Gontijo Batista

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This paper analyzes how the Socially Aware Design (SAwD) and the Value-oriented and Culturally Informed Approach (VCIA) design model can be used to develop an edutainment game for children with Attention Deficit Hyperactivity Disorder (ADHD). The SAwD approach seeks a design that considers new dimensions in human-computer interaction, such as culture, aesthetics, emotional and social aspects of the user's everyday experience. From this perspective, the game development was VCIA model-based, including the users in the design process through participatory methodologies, considering their behavioral patterns, culture, and values. This is because values, beliefs, and behavioral patterns influence how technology is understood and used and the way it impacts people's lives. This model can be applied at different stages of design, which goes from explaining the problem and organizing the requirements to the evaluation of the prototype and the final solution. Thus, this paper aims to understand how this model can be used in the development of an edutainment game for children with ADHD. In the area of education and learning, children with ADHD have difficulties both in behavior and in school performance, as they are easily distracted, which is reflected both in classes and on tests. Therefore, they must perform tasks that are exciting or interesting for them, once the pleasure center in the brain is activated, it reinforces the center of attention, leaving the child more relaxed and focused. In this context, serious games have been used as part of the treatment of ADHD in children aiming to improve focus and attention, stimulate concentration, as well as be a tool for improving learning in areas such as math and reading, combining education and entertainment (edutainment). Thereby, as a result of the research, it was developed, in a participatory way, applying the VCIA model, an edutainment game prototype, for a mobile platform, for children between 8 and 12 years old.

Keywords: ADHD, edutainment, SAwD, VCIA

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Authors: Vijaya Chandra Tenneti

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The juvenile justice delivery system in India suffers from many lacunae at the operational level and ignores many dimensions of human rights guaranteed to the juvenile delinquents. The present study begins with the hypothesis that the existing justice delivery system seemingly ignores the basic tenets of the fair trial and systemic support to the delinquent juveniles in integrating them into the mainstream of society. As per the designed methodology, data has been collected from the unit of the present study, and other stakeholders, namely, Juvenile Justice Board, Observation Homes etc., of Warangal district of Telangana state, India. The study shows that there is the overemphasis on procedural laws. The juvenile integration programs are not effective. The administrators lack training. Juveniles lack formal education. The study indicates the incidents of juvenile crimes is on the rise and that the majority of the juvenile delinquents hold a low socio-economic profile. Another significant observation of the study is that the juvenile justice system lacks a holistic and human rights-centric approach.

Keywords: delinquency, human rights, juvenile justice, rehabilitation

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Authors: Tanimola Kazeem Abiodun

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In the paper, attempt was made to investigate the impact of international trade on economic growth at the disaggregate level both from the theoretical and economic angle. The study in its contribution examines this impact at the disaggregated level. To this end, a hypothesis was formulated to investigate the short ?run and long run impact of international trade on growth in the country. In the econometrics investigation that follow, international trade was disaggregated to export and imports and their short run and long run effect on growth was examined. Also, the aggregate international trade was also investigated to see the long run effects of its own growth. The results of the findings indicate that; both export and import impact significantly to growth in the short run. The long-run impact of export on growth was found to be positive, significant and stable both. Engle-Granger co integration test and error correlation mechanism were applied to these long run relationships. For the import, while the short run was found to be positive and significant on its impact on growth, the long run relationship was found to be negative but not significant. Therefore, it is thus recommended among others that the country should engage more on export promotion drives.

Keywords: international trade, disaggregated, import, export, econometrics, trade, economic growth, foreign trade, import, export

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Authors: Andreas Aceranti, Simonetta Vernocchi, Marco Colorato, Pozzaglio Carolina

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This work analyses the term sect or religious cult and the general traits of those groups and the people involved so as to better understand this unexpectedly popular reality. Some translations taken from research papers as well as academic articles are likewise taken into consideration. We have carried out an in-depth analysis of the topics presented. Firstly we defined magic related to religion and all the similarities and differences between magical thinking and religious thinking, religion, and superstition. Secondly, the term “sect” was defined, and the phenomenon was dealt with, along with the listing of all kinds of existing groups. Then we studied the recruitment process in general and recruitment according to the brainwashing theory. We then analysed the criminological aspects that entail their harmfulness with a particular focus on the structure of those religious communities and the theories regarding the people involved: leader, members, and the group, as it has its own pattern of behaviour and its conformism. Finally, we studied the ideology and the techniques of manipulation used, such as brainwashing, which got already introduced in previous chapters trying to explain this reality not only in theory but studying and trying to understand some of the most famous religious cults.

Keywords: psychological manipulation, brainwashing, love bombing, magic and religion

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Authors: Paul Okonkwo, Howard Smith

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This paper describes a methodology to integrate the Athena Vortex Lattice Aerodynamic Software for automated operation in a multivariate optimisation of the Blended Wing Body Aircraft. The Athena Vortex Lattice code developed at the Massachusetts Institute of Technology by Mark Drela allows for the aerodynamic analysis of aircraft using the vortex lattice method. Ordinarily, the Athena Vortex Lattice operation requires a text file containing the aircraft geometry to be loaded into the AVL solver in order to determine the aerodynamic forces and moments. However, automated operation will be required to enable integration into a multidisciplinary optimisation framework. Automated AVL operation within the JAVA design environment will nonetheless require a modification and recompilation of AVL source code into an executable file capable of running on windows and other platforms without the –X11 libraries. This paper describes the procedure for the integrating the FORTRAN written AVL software for automated operation within the multivariate design synthesis optimisation framework for the conceptual design of the BWB aircraft.

Keywords: aerodynamics, automation, optimisation, AVL, JNI

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Authors: Payam Hayati, Fateme Firoozbakht, Gholamhassan Azimi, Shahram Tangestaninejad

Abstract:

The synthesis of a photocatalytic adsorbent involved the integration of carbon dots (CD) into a metal-organic framework (MOF) of MIL-88B(Fe) using the solvothermal technique. Characterization of the resulting CD@MIL-88B(Fe) was conducted using various analytical methods, including X-ray-based microscopic and spectroscopic techniques, electrochemical impedance spectroscopy, UV–Vis, FT-IR, DRS, TGA, and photoluminescence (PL) analysis. The adsorbent demonstrated significant photocatalytic activity, achieving up to 92% and 90% removal of amphotericin B (AmB) and naproxen (Nap) from aqueous solutions under visible light, with an RSD value of around 5%. The study explored the factors influencing the degradation of pharmaceuticals and determined the optimal conditions for the process, including pH values of 3 and 4 for AmB and Nap, a photocatalyst concentration of 0.2 g L-1, and an H2O2 concentration ranging from 40 to 50 mM. Reactive oxidative species such as ⋅OH and ⋅O2 were identified through the examination of different scavengers. Additionally, the adsorption isotherm and kinetic studies revealed that the synthesized photocatalyst functions as an effective adsorbent, with maximum adsorption capacities of 42.5 and 121.5 mg g-1 for AmB and Nap, while also serving as a photocatalytic agent for removal purposes.

Keywords: fenton-like degradation, metal-organic frameworks, heterogenous photocatalysts, naproxen

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Authors: Diego Giuseppe Romano, Gianvito Apuleo, Jiri Duda

Abstract:

Mobility is one of the most important societal needs for amusement, business activities and health. Thus, transport needs are continuously increasing, with the consequent traffic congestion and pollution increase. Aeronautic effort aims at smarter infrastructures use and in introducing greener concepts. A possible solution to address the abovementioned topics is the development of Small Air Transport (SAT) system, able to guarantee operability from today underused airfields in an affordable and green way, helping meanwhile travel time reduction, too. In the framework of Horizon2020, EU (European Union) has funded the Clean Sky 2 SAT TA (Transverse Activity) initiative to address market innovations able to reduce SAT operational cost and environmental impact, ensuring good levels of operational safety. Nowadays, most of the key technologies to improve passenger comfort and to reduce community noise, DOC (Direct Operating Costs) and pilot workload for SAT have reached an intermediate level of maturity TRL (Technology Readiness Level) 3/4. Thus, the key technologies must be developed, validated and integrated on dedicated ground and flying aircraft demonstrators to reach higher TRL levels (5/6). Particularly, SAT TA focuses on the integration at aircraft level of the following technologies [1]: 1)    Low-cost composite wing box and engine nacelle using OoA (Out of Autoclave) technology, LRI (Liquid Resin Infusion) and advance automation process. 2) Innovative high lift devices, allowing aircraft operations from short airfields (< 800 m). 3) Affordable small aircraft manufacturing of metallic fuselage using FSW (Friction Stir Welding) and LMD (Laser Metal Deposition). 4)       Affordable fly-by-wire architecture for small aircraft (CS23 certification rules). 5) More electric systems replacing pneumatic and hydraulic systems (high voltage EPGDS -Electrical Power Generation and Distribution System-, hybrid de-ice system, landing gear and brakes). 6) Advanced avionics for small aircraft, reducing pilot workload. 7) Advanced cabin comfort with new interiors materials and more comfortable seats. 8) New generation of turboprop engine with reduced fuel consumption, emissions, noise and maintenance costs for 19 seats aircraft. (9) Alternative diesel engine for 9 seats commuter aircraft. To address abovementioned market innovations, two different platforms have been designed: Reference and Green aircraft. Reference aircraft is a virtual aircraft designed considering 2014 technologies with an existing engine assuring requested take-off power; Green aircraft is designed integrating the technologies addressed in Clean Sky 2. Preliminary integration of the proposed technologies shows an encouraging reduction of emissions and operational costs of small: about 20% CO₂ reduction, about 24% NO_x reduction, about 10 db (A) noise reduction at measurement point and about 25% DOC reduction. Detailed description of the performed studies, analyses and validations for each technology as well as the expected benefit at aircraft level are reported in the present paper.

Keywords: affordable, European, green, mobility, technologies development, travel time reduction

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Authors: James Rigor Camacho, Wansu Lim

Abstract:

Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

Procedia PDF Downloads 97

Authors: Raef Cherif, Houssine Bakkali, Wafaa El Khatiri, Yacine Yaddaden

Abstract:

The analysis of how vibrations are transmitted between components is required in many engineering applications. Transfer path analysis (TPA) has been a valuable engineering tool for solving Noise, Vibration, and Harshness (NVH problems using sub-structuring applications. The most challenging part of a TPA analysis is estimating the equivalent forces at the contact points between the active and the passive side. Component TPA in situ Method calculates these forces by inverting the frequency response functions (FRFs) measured at the passive subsystem, relating the motion at indicator points to forces at the interface. However, matrix inversion could pose problems due to the ill-conditioning of the matrices leading to inaccurate results. This paper establishes a TPA model for an academic system consisting of two plates linked by four springs. A numerical study has been performed to improve the interface forces identification. Several parameters are studied and discussed, such as the singular value rejection and the number and position of indicator points chosen and used in the inversion matrix.

Keywords: transfer path analysis, matrix inverse method, indicator points, SVD decomposition

Procedia PDF Downloads 75

Authors: Danielle Schneider, Ying Xie

Abstract:

Middle school science, technology, engineering, and math (STEM) teachers experience an exceptional challenge in the expectation to incorporate curricula that builds strong spatial reasoning skills on rudimentary geometry concepts. Because spatial ability is so closely tied to STEM students’ success, researchers are tasked to determine effective instructional practices that create an authentic learning environment within the immersive virtual reality learning environment (IVRLE). This study looked to investigate the effect of the IVRLE on middle school STEM students’ spatial reasoning skills as a methodology to benefit the STEM middle school students’ spatial reasoning skills. This experimental study was comprised of thirty 7th-grade STEM students divided into a treatment group that was engaged in an immersive VR platform where they engaged in building an object in the virtual realm by applying spatial processing and visualizing its dimensions and a control group that built the identical object using a desktop computer-based, computer-aided design (CAD) program. Before and after the students participated in the respective “3D modeling” environment, their spatial reasoning abilities were assessed using the Middle Grades Mathematics Project Spatial Visualization Test (MGMP-SVT). Additionally, both groups created a physical 3D model as a secondary measure to measure the effectiveness of the IVRLE. The results of a one-way ANOVA in this study identified a negative effect on those in the IVRLE. These findings suggest that with middle school students, virtual reality (VR) proved an inadequate tool to benefit spatial relation skills as compared to desktop-based CAD.

Keywords: virtual reality, spatial reasoning, CAD, middle school STEM

Procedia PDF Downloads 76