Search results for: physical learning environment

Authors: Susanna Graziano, Lydia Krstic Ward

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The purpose of this presentation is to demonstrate the steps of using multimedia and collaborative platforms in project-based learning. The presentation will demonstrate the stages of the learning project with various components of independent and collaborative learning, where students research the topic, share information, prepare a survey, use social media (Facebook, Instagram, WhasApp) and collaborative platforms (wikispaces.com and Google docs) to collect, analyze and process data, then produce reports and logos to be displayed as a final product. At the beginning of the presentation participants will answer a questionnaire about project based learning and share their experience on using social media, real–world project work and collaborative learning. Using a PPP, the presentation will walk participants through the steps of a completed project where tertiary education students are involved in putting together a multimedia campaign for safe driving in Kuwait. The research component of the project entails taking a holistic view on the problem of the high death rate in traffic accidents. The final goal of the project is to lead students to raise public awareness about the importance of safe driving. The project steps involve using the social media and collaborative platforms for collecting data and sharing the required materials to be used in the final product – a display of written reports, slogans and videos, as well as oral presentations. The same structure can be used to organize a multimedia campaign focusing on other issues, whilst scaffolding on students’ ability to brainstorm, retrieve information, organize it and engage in collaborative/ cooperative learning whilst being immersed in content-based learning as well as in authentic tasks. More specifically, the project we carried out at Box Hill College was a real-world one and involved a multimedia Campaign for Safe Driving since reckless driving is one of the major problems in the country. The idea for the whole project started by a presentation given by a board member of the Kuwaiti Society for Traffic Safety who was invited to college and spoke about: • Driving laws in the country, • What causes car accidents, • Driving safety tips. The principal goal of this project was to let students consider problems of traffic in Kuwait from different points of view. They also had to address the number and causes of accidents, evaluate the effectiveness of the local traffic law in order to send a warning about the importance of safe driving and, finally, suggest ways of its improvement. Benefits included: • Engagement, • Autonomy, • Motivation, • Content knowledge, • Language mastery, • Enhanced critical thinking, • Increased metacognitive awareness, • Improved social skills, • Authentic experience.

Keywords: social media, online learning platforms, collaborative platforms, project based learning

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Authors: M. R. Noor El-Din, Marwa R. Mishrif, R. E. Morsi, E. A. El-Sharaky, M. E. Haseeb, Rania T. M. Ghanem

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This paper studies the physical and rheological behaviours of water/in/diesel fuel nanoemulsions prepared by modified low energy method. Twenty of water/in/diesel fuel nanoemulsions were prepared using mixed nonionic surfactants of sorbitan monooleate and polyoxyethylene sorbitan trioleate (MTS) at Hydrophilic-Lipophilic Balance (HLB) value of 10 and a working temperature of 20°C. The influence of the prepared nanoemulsions on the physical properties such as kinematic viscosity, density, and calorific value was studied. Also, nanoemulsion systems were subjected to rheological evaluation. The effect of water loading percentage (5, 6, 7, 8, 9 and 10 wt.%) on rheology was assessed at temperatures range from 20 to 60°C with temperature interval of 10 for time lapse 0, 1, 2 and 3 months, respectively. Results show that all of the sets nanoemulsions exhibited a Newtonian flow character of low-shear viscosity in the range of 132 up to 191 1/s, and followed by a shear-thinning region with yield value (Non-Newtonian behaviour) at high shear rate for all water ratios (5 to 10 wt.%) and at all test temperatures (20 to 60°C) for time ageing up to 3 months. Also, the viscosity/temperature relationship of all nanoemulsions fitted well Arrhenius equation with high correlation coefficients that ascertain their Newtonian behavior.

Keywords: alternative fuel, nanoemulsion, surfactant, diesel fuel

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Authors: Jean Marie Tshimula, Atsushi Togashi

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We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: I. Gahlouz, A. Chellil

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The paper concerns the estimation of system components faults by using an unknown inputs observer. To reach this goal, we used the Bond Graph approach to physical modelling. We showed that this graphical tool is allowing the representation of system components faults as unknown inputs within the state representation of the considered physical system. The study of the causal and structural features of the system (controllability, observability, finite structure, and infinite structure) based on the Bond Graph approach was hence fulfilled in order to design an unknown inputs observer which is used for the system component fault estimation.

Keywords: estimation, bond graph, controllability, observability

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Authors: Joan Esper Kuhnly, Jess Holden, Lynn Shelley, Nicole Kuhnly

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Empathy serves as a foundational nursing principle inherent in the nurse’s ability to form those relationships from which to care for patients. Evidence supports, including empathy in nursing and healthcare education, but there is limited data on what methods are effective to do so. Building evidence supports experiential and interactive learning methods to be effective for students to gain insight and perspective from a personalized experience. The purpose of this project is to evaluate learning activities designed to promote the attainment of empathic behaviors across 5 levels of the nursing curriculum. Quantitative analysis will be conducted on data from pre and post-learning activities using the Toronto Empathy Questionnaire. The main hypothesis, that simulation learning activities will increase empathy, will be examined using a repeated measures Analysis of Variance (ANOVA) on Pre and Post Toronto Empathy Questionnaire scores for three simulation activities (Stroke, Poverty, Dementia). Pearson product-moment correlations will be conducted to examine the relationships between continuous demographic variables, such as age, credits earned, and years practicing, with the dependent variable of interest, Post Test Toronto Empathy Scores. Krippendorff’s method of content analysis will be conducted to identify the quantitative incidence of empathic responses. The researchers will use Colaizzi’s descriptive phenomenological method to describe the students’ simulation experience and understand its impact on caring and empathy behaviors employing bracketing to maintain objectivity. The results will be presented, answering multiple research questions. The discussion will be relevant to results and educational pedagogy in the nursing curriculum as they relate to the attainment of empathic behaviors.

Keywords: curriculum, empathy, nursing, simulation

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Authors: John Zanetich

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Designing an educational activity that encourages inquiry and collaboration is key to engaging students in meaningful learning. Educational Information and Communications Technology (EICT) plays an important role in facilitating cooperative and collaborative learning in the classroom. The EICT also facilitates students’ learning and development of the critical thinking skills needed to solve real world problems. Projects and activities based on constructivism encourage students to embrace complexity as well as find relevance and joy in their learning. It also enhances the students’ capacity for creative and responsible real-world problem solving. Classroom activities based on constructivism offer students an opportunity to develop the higher–order-thinking skills of defining problems and identifying solutions. Participating in a classroom project is an activity for both acquiring experiential knowledge and applying new knowledge to practical situations. It also provides an opportunity for students to integrate new knowledge into a skill set using reflection. Classroom projects can be developed around a variety of learning objects including social media, knowledge management and learning communities. The construction of meaning through project-based learning is an approach that encourages interaction and problem-solving activities. Projects require active participation, collaboration and interaction to reach the agreed upon outcomes. Projects also serve to externalize the invisible cognitive and social processes taking place in the activity itself and in the student experience. This paper describes a classroom project designed to elicit interactions by helping students to unfreeze existing knowledge, to create new learning experiences, and then refreeze the new knowledge. Since constructivists believe that students construct their own meaning through active engagement and participation as well as interactions with others. knowledge management can be used to guide the exchange of both tacit and explicit knowledge in interpersonal interactions between students and guide the construction of meaning. This paper uses an action research approach to the development of a classroom project and describes the use of technology, social media and the active use of tacit knowledge in the college classroom. In this project, a closed group Facebook page becomes the virtual classroom where interaction is captured and measured using engagement analytics. In the virtual learning community, the principles of knowledge management are used to identify the process and components of the infrastructure of the learning process. The project identifies class member interests and measures student engagement in a learning community by analyzing regular posting on the Facebook page. These posts are used to foster and encourage interactions, reflect a student’s interest and serve as reaction points from which viewers of the post convert the explicit information in the post to implicit knowledge. The data was collected over an academic year and was provided, in part, by the Google analytic reports on Facebook and self-reports of posts by members. The results support the use of active tacit knowledge activities, knowledge management and social media to enhance the student learning experience and help create the knowledge that will be used by students to construct meaning.

Keywords: constructivism, knowledge management, tacit knowledge, social media

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Authors: Hyoshin Kim

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Most post-secondary educational institutions have offered a wide variety of professional development programs and resources in order to advance the quality of education. Such programs are designed to support faculty members by focusing on topics such as course design, behavioral learning objectives, class discussion, and evaluation methods. These are based on good intentions and might help both new and experienced educators. However, the fundamental flaw is that these ‘effective methods’ are assumed to work regardless of what we teach and whom we teach. This paper is focused on intercultural intelligence and its application to education. It presents a comprehensive literature review on context and cultural diversity in terms of beliefs, values and worldviews. What has worked well with a group of homogeneous local students may not work well with more diverse and international students. It is because students hold different notions of what is means to learn or know something. It is necessary for educators to move away from certain sets of generic teaching skills, which are based on a limited, particular view of teaching and learning. The main objective of the research is to expand our teaching strategies by incorporating what students bring to the course. There have been a growing number of resources and texts on teaching international students. Unfortunately, they tend to be based on the deficiency model, which treats diversity not as strengths, but as problems to be solved. This view is evidenced by the heavy emphasis on assimilationist approaches. For example, cultural difference is negatively evaluated, either implicitly or explicitly. Therefore the pressure is on culturally diverse students. The following questions reflect the underlying assumption of deficiencies: - How can we make them learn better? - How can we bring them into the mainstream academic culture?; and - How can they adapt to Western educational systems? Even though these questions may be well-intended, there seems to be something fundamentally wrong as the assumption of cultural superiority is embedded in this kind of thinking. This paper examines how educators can incorporate intercultural intelligence into the course design by utilizing a variety of tools such as pre-course activities, peer learning and reflective learning journals. The main goal is to explore ways to engage diverse learners in all aspects of learning. This can be achieved by activities designed to understand their prior knowledge, life experiences, and relevant cultural identities. It is crucial to link course material to students’ diverse interests thereby enhancing the relevance of course content and making learning more inclusive. Internationalization of higher education can be successful only when cultural differences are respected and celebrated as essential and positive aspects of teaching and learning.

Keywords: intercultural competence, intercultural intelligence, teaching and learning, post-secondary education

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Authors: Ilgoun Kim, Jongpil Jeong

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Recently, a connected industrial parks (CIPs) architecture using new technologies such as RFID, cloud computing, CPS, Big Data, 5G 5G, IIOT, VR-AR, and ventral AI algorithms based on IoT has been proposed. This researcher noted the vehicle junction problem (VJP) as a more specific detail of the CIPs architectural models. The VJP noted by this researcher includes 'efficient AI physical connection challenges for vehicles' through ventilation, 'financial and financial issues with complex vehicle physical connections,' and 'welfare and working conditions of the performing personnel involved in complex vehicle physical connections.' In this paper, we propose a public solution architecture for the 'electronic financial problem of complex vehicle physical connections' as a detailed task during the vehicle junction problem (VJP). The researcher sought solutions to businesses, consumers, and Korean social problems through technological advancement. We studied how the beneficiaries of technological development can benefit from technological development with many consumers in Korean society and many small and small Korean company managers, not some specific companies. In order to more specifically implement the connected industrial parks (CIPs) architecture using the new technology, we noted the vehicle junction problem (VJP) within the smart factory industrial complex and noted the process of achieving the vehicle junction problem performance among several electronic processes. This researcher proposes a more detailed, integrated public finance enterprise architecture among the overall CIPs architectures. The main details of the public integrated financial enterprise architecture were largely organized into four main categories: 'business', 'data', 'technique', and 'finance'.

Keywords: enterprise architecture, IT Finance, smart logistics, CIPs

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Authors: Mohammed Nabeel Khan, C. Perisamy

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Convective vortices are normal highlights of air that ingest lower-entropy-energy at higher temperatures than they dismiss higher-entropy-energy to space. By means of the thermodynamic proficiency, it has been anticipated that the force of convective vortices relies upon the profundity of the convective layer. The atmospheric vortex engine is proposed as a gadget for delivering mechanical energy by methods for artificially produced vortex. The task of the engine is in view of the certainties that the environment is warmed from the base and cooled from the top. By generation of the artificial vortex, it is planned to take out the physical solar updraft tower and decrease the capital of the solar chimney power plants. The study shows the essentials of the atmospheric vortex engine, furthermore, audits the cutting edge in subject. Moreover, the study talks about a thought on using the solar energy as heat source to work the framework. All in all, the framework is attainable and promising for electrical power production.

Keywords: AVE, atmospheric vortex engine, atmosphere, updraft, vortex

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Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

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Authors: Clement Temaneh-Nyah, Josiah Makiche, Josephine Nujoma

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This paper considers the characterisation of a complex electromagnetic environment due to multiple sources of electromagnetic radiation as a five-dimensional surface which can be described by a set of several surface sections including: instant EM field intensity distribution maps at a given frequency and altitude, instantaneous spectrum at a given location in space and the time evolution of the electromagnetic field spectrum at a given point in space. This characterization if done over time can enable the exposure levels of Radio Frequency Radiation at every point in the analysis area to be determined and results interpreted based on comparison of the determined RFR exposure level with the safe guidelines for general public exposure given by recognised body such as the International commission on non-ionising radiation protection (ICNIRP), Institute of Electrical and Electronic Engineers (IEEE), the National Radiation Protection Authority (NRPA).

Keywords: complex electromagnetic environment, electric field strength, mathematical models, multiple sources

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Authors: Mahfoud Benzerzour, Mouhamadou Amar, Nor-edine Abriak

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In this study, a sediment was used as a secondary raw material in cement substitution with prior treatment. The treatment adopted is a physical treatment involving grinding and separation to obtain different fractions, using a dry method (1 mm, 250µm, 120µm) and washing method (250µm and 120µm). They were subsequently heat treated at temperatures of 650°C, 750°C and 850°C for 1 hour and 3 hours, in order to enable chemical activation by decarbonation or by pozzolanic activation of the material. Different characterization techniques were performed. The determination of main physical and chemical characteristics was obtained through multiple tests: particle size distribution, specific density, the BET surface area, the initial setting time and hydration heat calorimetry Langavant. The chemical tests include: ATG analysis, X-ray diffractometry (XRD) and X-ray fluorescence (XRF) which were used to quantify the fractions, phases and chemical elements present. Compression tests were performed conforming NF EN 196-1 French standard, over terms of 7 days - 14 days - 28 days and 60 days on all formulated mortars: reference mortar based on 100% CEM I 52.5N binder and cement substituted mortars with 8% and 15% by treated sediment. This clearly evidenced contribution due to the chemical activity which was confirmed by calorimetry monitoring and strength investigation.

Keywords: sediment, characterization, grinding, heat treatment, substitution

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Authors: Panarat Saengpanya

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There were five objectives in this study including the study of housing type with water environment, the physical and mechanical properties of the buoy material, the mechanical properties of the buoy models, the floating of the buoy models and the relationship between the civil engineering parameters and the floating of the buoy. The buoy examples made from Expanded Polystyrene (EPS) covered by 5 mm thickness of mortar with the equal thickness on each side. Specimens are 0.05 m cubes tested at a displacement rate of 0.005 m/min. The existing test method used to assess the parameters relationship is ASTM C 109 to provide comparative results. The results found that the three type of housing with water environment were Stilt Houses, Boat House, and Floating House. EPS is a lightweight material that has been used in engineering applications since at least the 1950s. Its density is about a hundredth of that of mortar, while the mortar strength was found 72 times of EPS. One of the advantage of composite is that two or more materials could be combined to take advantage of the good characteristics of each of the material. The strength of the buoy influenced by mortar while the floating influenced by EPS. Results showed the buoy example compressed under loading. The Stress-Strain curve showed the high secant modulus before reached the peak value. The failure occurred within 10% strain then the strength reduces while the strain was continuing. It was observed that the failure strength reduced by increasing the total volume of examples. For the buoy examples with same area, an increase of the failure strength is found when the high dimension is increased. The results showed the relationship between five parameters including the floating level, the bearing capacity, the volume, the high dimension and the unit weight. The study found increases in high of buoy lead to corresponding decreases in both modulus and compressive strength. The total volume and the unit weight had relationship with the bearing capacity of the buoy.

Keywords: floating house, buoy, floating structure, EPS

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Authors: Maya Kagan, Michal Itzick, Patricia Tal-Katz

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Social workers hold a variety of roles and practices, and one of these involves the care, treatment, and rehabilitation of disabled people. The current study assesses the association between demographic factors, attitudes towards social workers, the stigma attached to seeking social worker help, perceived social support, and psychological distress - and the self-reported likelihood of seeking social worker help, among people with physical disabilities (PWPD) in Israel. Data collection utilized structured questionnaires, administered to a sample of 435 PWPD. Statistical analyses were done using SPSS software. The findings suggest that women, older respondents, people with more positive attitudes towards social workers, with higher levels of psychological distress and of social support, and with a lower level of stigma, reported a greater likelihood of seeking social worker help. The study's conclusion is that there are certain avoidance factors among PWPD that might discourage them from seeking professional social worker help. Therefore, it is important that social workers identify these factors and develop interventions aimed at encouraging PWPD to seek professional social worker help in case of need, and also develop practices adjusted to PWPD's unique needs.

Keywords: attitudes towards social workers, people with physical disabilities, perceived social support, psychological distress, seeking help, stigma

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Authors: Han Hyuk Cho, Hanik Jo

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In recent years, coding education has been globally emphasized, and the Free Semester System and coding education were introduced to the public schools from the beginning of 2016 and 2018 respectively in Korea. With the introduction of the Free Semester System and the rising demand of Computational Thinking (CT) capacity, this paper aims to design ‘Coding Environment’ and Minecraft-like Turtlecraft in which learners can design and construct mathematical objects through mathematical symbolic expressions. Students can transfer the constructed mathematical objects to the Turtlecraft environment (open-source codingmath website), and also can print them out through 3D printers. Furthermore, we design learnable mathematics and coding curriculum by representing the figurate numbers and patterns in terms of executable expression in the coding context and connecting them to algebraic symbols, which will allow students to experience mathematical patterns and symbolic coding expressions.

Keywords: coding education, computational thinking, mathematics education, TurtleMAL and Turtlecraft

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Authors: Daria Druzhinenko- Silhan, Patrick Schmoll

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Childhood obesity is one of the important problem in domain of health care. During two recent decades we are observing a real epidemic of this noninfectious illness. Its consequences are hard: cardio-vascular disease; diabetes; arthrosis etc. (OMS, 2012) Keep Healthy Kids  » study aims to create a new system of accompanying of childhood obesity based on new technologies as mobile applications or serious video-games. We realize a support-study which aims to understand motivations, psychological dynamite and family's impact on weight-loss process in childhood. Sample: 65 children from 7 to 10 years old accompanied by special Care Center in France. Methodology: we proceed by an innovative approach that bases on quantitative and qualitative methods of data collection. We focus our proposal on data collected from medical files. We are also realizing individual assessment (still ongoing) that aims to understand psychological profiles of obese children and their family dynamic. Results: Only 16,9% of children asked for medical accompanying of obesity. We noted that the most important reason to come to the care Center was the fact of mates' scoffs (46,2%°), the second one was the appearance or look (40 %). We found out that the self-image of these children in self-evaluation questionnaire was described mostly as rather good (46,2) or good (28,2%); the most part of children evaluated their well-being as rather good (29,7%) or good (51,4%). In interviews children had tendency to not recall why they came to the Care Center. Discussion : These results permit us to make a hypothesis that children suffering of overweight or obesity are not clearly aware why they must loose weight. It was rather the peer environment that pointed out the problem of overweight for them. So the motivation to loose weight is mostly supported by environment. We suppose that it is a « weak-point » of their motivation and it can be over-come using serious video-games supporting physical activity that can make deviate the motivation from « to loose weight for be looked better by the others » into « have fun and feeling me better ».

Keywords: childhood obesity, motivation, weight-loss, serious video-game

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Authors: Gebreegziabher Hailu Gebrecherkos

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This study examines the effectiveness of GeoGebra in developing the conceptual understanding of transformation geometry among Grade 11 students. Utilizing a quasi-experimental design, the research compares the learning outcomes of students who engaged with GeoGebra against those who received traditional instruction. Pre- and post-tests were administered to assess students' grasp of key transformation concepts, including translations, rotations, reflections, and dilations. Additionally, qualitative data were gathered through student interviews and classroom observations to explore their experiences and perceptions of using GeoGebra. Results indicate that students utilizing GeoGebra showed significantly greater improvement in their understanding of transformation geometry concepts. The interactive features of GeoGebra facilitated visualization and exploration, leading to enhanced engagement and deeper conceptual insights. The findings underscore the potential of GeoGebra as a powerful educational tool that not only fosters mathematical understanding but also accommodates diverse learning styles in the classroom. This study contributes valuable insights for educators seeking to improve the teaching and learning of transformation geometry in secondary education.

Keywords: calculus, conceptual understanding, GeoGebra, transformation geometry

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Authors: Ayomide Oyedele

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In the dynamic landscape of cybersecurity, "Strategic Cyber Sentinel" emerges as a revolutionary framework, transcending traditional approaches. This paper pioneers a holistic strategy, weaving together threat intelligence, machine learning, and adaptive defenses. Through meticulous real-world simulations, we demonstrate the unprecedented resilience of our framework against evolving cyber threats. "Strategic Cyber Sentinel" redefines proactive threat mitigation, offering a robust defense architecture poised for the challenges of tomorrow.

Keywords: cybersecurity, resilience, threat intelligence, machine learning, adaptive defenses

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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Authors: Olga Guseynova

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Being an individual activity, the memorizing process is affected to a greater degree by the individual variables; therefore, one of the decisive factors influencing the memorization is students’ individual characteristics. Based on an extensive literature study in the domains of piano education, psychology, and neuroscience, this comprehensive research was designed in order to develop three memorizing strategies that are reflective of individual students’ learning modalities (visual, kinesthetic and auditory) applied to the piano education. The design of the study required an interdisciplinary approach which incorporated the outcome of neuropsychological and pedagogic experiments. The objectives were to determine the interaction between the process of perception and the process of memorizing music; to systematize the methods of memorizing piano sheet music in accordance with the specifics of perception types; to develop Piano Memorization Inventory (PMI) and the Three Memorizing Strategies (TMS). The following research methods were applied: a method of interdisciplinary analysis and synthesis, a method of non-participant observation. As a result of literature analysis, the following conclusions were made: the majority of piano teachers and piano students participated in the surveys, had not used and usually had not known any memorizing strategy regarding learning styles. As a result, they had used drilling as the main strategy of memorizing. The Piano Memorization Inventory and Three Memorizing Strategies developed by the author of the research were based on the observation and findings of the previous researches and considered the experience of pedagogical and neuropsychological studies.

Keywords: interdisciplinary approach, memorizing strategies, perceptual learning styles, piano memorization inventory

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Prakash Singh, Piet Maphodisa Kgohlo

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Knowledge-worker productivity is one of the biggest leadership challenges facing all organizations in the twenty-first century. It cannot be denied that knowledge-worker productivity affects all organizations. The work and the workforce are both undergoing greater changes currently than at any time, since the beginning of the industrial revolution two centuries ago. Employees welcome collegial teaming (CT) as an innovative way to develop their work-integrated learning competencies. Human resource development policies must evoke the symbiotic relationship between CT and work-integrated learning, seeing that employees need to be endowed with the competence to move from one skill to another, as each one becomes obsolete, and to simultaneously develop their cognitive and emotional intelligence. The outcome of this relationship must culminate in the development of highly productive knowledge-workers. While this study focuses on teachers, the conceptual framework and the findings of this research can be beneficial for any organization, public or private sector, business or non-business. Therefore, in this quantitative study, the benefits of CT are considered in developing human resources to sustain knowledge-worker productivity. The ANOVA p-values reveal that the majority of teachers agree that CT can empower them to overcome the challenges of managing curriculum change. CT can equip them with continuous and sustained learning, growth and improvement, necessary for knowledge-worker productivity. This study, therefore, confirms that CT benefits all workers, immaterial of their age, gender or experience. Hence, this exploratory research provides a new perspective of CT in addressing knowledge-worker productivity when organizational change alters the vision of the organization.

Keywords: collegial teaming, human resource development, knowledge-worker productivity, work-integrated learning

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Authors: Chiung-Hui Chen

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With advancements in science and technology, the concept of the Internet of Things (IoT) has gradually developed. The development of the intelligent environment adds intelligence to objects in the living space by using the IoT. In the smart environment, when multiple users share the living space, if different service requirements from different users arise, then the context-aware system will have conflicting situations for making decisions about providing services. Therefore, the purpose of establishing a communication and negotiation mechanism among objects in the intelligent environment is to resolve those service conflicts among users. This study proposes developing a decision-making methodology that uses “Event Agents” as its core. When the sensor system receives information, it evaluates a user’s current events and conditions; analyses object, location, time, and environmental information; calculates the priority of the object; and provides the user services based on the event. Moreover, when the event is not single but overlaps with another, conflicts arise. This study adopts the “Multiple Events Correlation Matrix” in order to calculate the degree values of incidents and support values for each object. The matrix uses these values as the basis for making inferences for system service, and to further determine appropriate services when there is a conflict.

Keywords: internet of things, intelligent object, event agents, negotiation mechanism, degree of similarity

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Authors: Han Bai, Lemei Yu, Tong Zhang, Doudou Xie, Liang Zhao

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The brightness changes at highway tunnel entrance and exit have an effect on the physical and psychological conditions of drivers. It is more conducive for examining driving safety with quantitative analysis of the physical and psychological characteristics of drivers to determine the speed limit sign locations at the tunnel entrance and exit sections. In this study, the physical and psychological effects of tunnels on traffic sign recognition of drivers are analyzed; subsequently, experiments with the assistant of Eyelink-II Type eye movement monitoring system are conducted in the typical tunnels in Ji-Qing freeway and Xi-Zha freeway, to collect the data of eye movement indexes “Fixation Duration” and “Eyeball Rotating Speed”, which typically represent drivers' mental load and visual characteristics. On this basis, the paper establishes a visual recognition model for the speed limit signs at the highway tunnel entrances and exits. In combination with related standards and regulations, it further presents the recommended values for locating speed limit signs under different tunnel conditions. A case application on Panlong tunnel in Ji-Qing freeway is given to generate the helpful improvement suggestions.

Keywords: driver psychological load, eye movement index, speed limit sign location, tunnel entrance and exit

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Authors: Nuttha Kirdsinsap, Watchaneeporn Setthasakko

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This paper aims to gain opinions and perspectives of Certified Public Accountants (CPA) in Thailand regarding the driven force of Integrated Reporting. It employs in-depth interviews with CPA from different big 4 audits firms in Thailand, including PWC, Ernst and Young, Deloitte, and KPMG. It is found that the driven force of Integrated Reporting made CPA in Thailand awaken to the big change that is coming in the future, and it is said to be another big learning and integrating period between certified public accountants and other professionals (for example, engineers, environmentalists and lawyers), which, certified public accountants in Thailand will have to push themselves so hard to catch up.

Keywords: integrated reporting, learning, knowledge, certified public accountants, Thailand

Procedia PDF Downloads 267

Authors: Matjaz Prek

Abstract:

Impact of three different combinations of cooling and ventilation systems on the indoor environmental quality (IEQ) has been studied. Comparison of chilled ceiling cooling in combination with displacement ventilation, cooling with fan coil unit and cooling with flat wall displacement outlets was performed. All three combinations were evaluated from the standpoint of whole-body and local thermal comfort criteria as well as from the standpoint of ventilation effectiveness. The comparison was made on the basis of numerical simulation with DesignBuilder and Fluent. Numerical simulations were carried out in two steps. Firstly the DesignBuilder software environment was used to model the buildings thermal performance and evaluation of the interaction between the environment and the building. Heat gains of the building and of the individual space, as well as the heat loss on the boundary surfaces in the room, were calculated. In the second step Fluent software environment was used to simulate the response of the indoor environment, evaluating the interaction between building and human, using the simulation results obtained in the first step. Among the systems presented, the ceiling cooling system in combination with displacement ventilation was found to be the most suitable as it offers a high level of thermal comfort with adequate ventilation efficiency. Fan coil cooling has proved inadequate from the standpoint of thermal comfort whereas flat wall displacement outlets were inadequate from the standpoint of ventilation effectiveness. The study showed the need in evaluating indoor environment not solely from the energy use point of view, but from the point of view of indoor environmental quality as well.

Keywords: cooling, ventilation, thermal comfort, ventilation effectiveness, indoor environmental quality, IEQ, computational fluid dynamics

Procedia PDF Downloads 182

Authors: Tahsin Shameem, Chowdhury Sadman Jahan, Mohammad Alam

Abstract:

Interest about Net Zero Energy Buildings have gained traction in recent years following the need to sustain energy consumption with generations on site and to reduce dependence on grid supplied energy from large plants using fossil fuel. With this end in view, building integrated photovoltaics are being studied attempting to utilize all exterior facades of a building to generate power. In this paper, we have looked at the physical parameters defining a dye sensitized solar cell (DSSC) and discussed their impact on energy harvest. Following our discussion and experimental data obtained from literature, we have attempted to optimize these physical parameters accordingly so as to allow maximum light absorption for a given active layer thickness. We then modified a planer DSSC design with our optimized properties to allow adequate light transmission which demonstrated a high fill factor and an External Quantum Efficiency (EQE) of greater than 9% by computer aided design and simulation. In conclusion, a DSSC based solar window with such high output values even after such high light transmission through it definitely flags a promising future for this technology and our work elicits the need for further study and practical experimentation.

Keywords: net zero energy building, integrated photovoltaics, dye sensitized solar cell, fill factor, External Quantum Efficiency

Procedia PDF Downloads 137

Authors: Albatool Al Abdulwahid, Bayan Shakally, Mariam Mohamed, Wed Almokri

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Artificial intelligence has infiltrated every part of our life and every field we can think of. With technical developments, artificial intelligence applications are becoming more prevalent. We chose ELSA speak because it is a magnificent example of Artificial intelligent applications, ELSA speak is a smartphone application that is free to download on both IOS and Android smartphones. ELSA speak utilizes artificial intelligence to help non-native English speakers pronounce words and phrases similar to a native speaker, as well as enhance their English skills. It employs speech-recognition technology that aids the application to excel the pronunciation of its users. This remarkable feature distinguishes ELSA from other voice recognition algorithms and increase the efficiency of the application. This study focused on evaluating ELSA speak application, by testing the degree of effectiveness based on survey questions. The results of the questionnaire were variable. The generality of the participants strongly agreed that ELSA has helped them enhance their pronunciation skills. However, a few participants were unconfident about the application’s ability to assist them in their learning journey.

Keywords: ELSA speak application, artificial intelligence, speech-recognition technology, language learning, english pronunciation

Procedia PDF Downloads 102

Authors: Amreth Chandrasehar

Abstract:

Machine Learning (ML) Models are developed and run in production to solve various use cases that help organizations to be more efficient and help drive the business. But this comes at a massive development cost and lost business opportunities. According to the Gartner report, 85% of data science projects fail, and one of the factors impacting this is not paying attention to Model Observability. Model Observability helps the developers and operators to pinpoint the model performance issues data drift and help identify root cause of issues. This paper focuses on providing insights into incorporating model observability in model development and operationalizing it in production.

Keywords: model observability, monitoring, drift detection, ML observability platform

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Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

Abstract:

Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

Procedia PDF Downloads 190