Search results for: Gagne’s learning model
15497 Differences in Preschool Educators' and Parents' Interactive Behavior during a Cooperative Task with Children
Authors: Marina Fuertes
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Introduction: In everyday life experiences, children are solicited to cooperate with others. Often they perform cooperative tasks with their parents (e.g., setting the table for dinner) or in school. These tasks are very significant since children may learn to turn taking in interactions, to participate as well to accept others participation, to trust, to respect, to negotiate, to self-regulate their emotions, etc. Indeed, cooperative tasks contribute to children social, motor, cognitive and linguistic development. Therefore, it is important to study what learning, social and affective experiences are provided to children during these tasks. In this study, we included parents and preschool educators. Parents and educators are both significant: educative, interactive and affective figures. Rarely parents and educators behavior have been compared in studies about cooperative tasks. Parents and educators have different but complementary styles of interaction and communication. Aims: Therefore, this study aims to compare parents and educators' (of both genders) interactive behavior (cooperativity, empathy, ability to challenge the child, reciprocity, elaboration) during a play/individualized situation involving a cooperative task. Moreover, to compare parents and educators' behavior with girls and boys. Method: A quasi-experimental study with 45 dyads educators-children and 45 dyads with parents and their children. In this study, participated children between 3 and 5 years old and with age appropriate development. Adults and children were videotaped using a variety of materials (e.g., pencils, wood, wool) and tools (e.g., scissors, hammer) to produce together something of their choice during 20-minutes. Each dyad (one adult and one child) was observed and videotaped independently. Adults and children agreed and consented to participate. Experimental conditions were suitable, pleasant and age appropriated. Results: Findings indicate that parents and teachers offer different learning experiences. Teachers were more likely to challenged children to explore new concepts and to accept children ideas. In turn, parents gave more support to children actions and were more likely to use their own example to teach children. Multiple regression analysis indicates that parent versus educator status predicts their behavior. Gender of both children and adults affected the results. Adults acted differently with girls and boys (e.g., adults worked more cooperatively with girls than boys). Male participants supported more girls participation rather than boys while female adults allowed boys to make more decisions than girls. Discussion: Taking our results and past studies, we learn that different qualitative interactions and learning experiences are offered by parents, educators according to parents and children gender. Thus, the same child needs to learn different cooperative strategies according to their interactive patterns and specific context. Yet, cooperative play and individualized activities with children generate learning opportunities and benefits children participation and involvement.Keywords: early childhood education, parenting, gender, cooperative tasks, adult-child interaction
Procedia PDF Downloads 32915496 English for Specific Purposes: Its Definition, Characteristics, and the Role of Needs Analysis
Authors: Karima Tayaa, Amina Bouaziz
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The rapid expansion in the scientific fields and the growth of communication technology increased the use of English as international language in the world. Hence, over the past few decades, many researchers have been emphasizing on how the teaching and learning of English as a foreign or as an additional language can best help students to perform successfully. English for specific purpose is today quite literally regarded as the most global language discipline which existed practically in every country in the world. ESP (English for Specific Purposes) involves teaching and learning the specific skills and language needed by particular learners for a particular purpose. The P in ESP is always a professional purpose which is a set of skills that learners currently need in their work or will need in their professional careers. It has had an early origin since 1960’s and has grown to become one of the most prominent of English language teaching today. Moreover, ESP learners are usually adults who have some quittances with English and learn the language so as to communicate and perform particular profession. Related activities are based on specific purposes and needs. They are integrated into subject matter area important to the learners. Unlike general English which focuses on teaching general language courses and all four language skills are equally stressed, ESP and practically needs analysis determine which language skills are the most needed by the learners and syllabus designed accordingly. This paper looked into the origin, characteristics, development of ESP, the difference between ESP and general English. Finally, the paper critically reviews the role of needs analysis in the ESP.Keywords: English language teaching, English for general purposes, English for specific purposes, needs analysis
Procedia PDF Downloads 41015495 A Machine Learning Framework Based on Biometric Measurements for Automatic Fetal Head Anomalies Diagnosis in Ultrasound Images
Authors: Hanene Sahli, Aymen Mouelhi, Marwa Hajji, Amine Ben Slama, Mounir Sayadi, Farhat Fnaiech, Radhwane Rachdi
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Fetal abnormality is still a public health problem of interest to both mother and baby. Head defect is one of the most high-risk fetal deformities. Fetal head categorization is a sensitive task that needs a massive attention from neurological experts. In this sense, biometrical measurements can be extracted by gynecologist doctors and compared with ground truth charts to identify normal or abnormal growth. The fetal head biometric measurements such as Biparietal Diameter (BPD), Occipito-Frontal Diameter (OFD) and Head Circumference (HC) needs to be monitored, and expert should carry out its manual delineations. This work proposes a new approach to automatically compute BPD, OFD and HC based on morphological characteristics extracted from head shape. Hence, the studied data selected at the same Gestational Age (GA) from the fetal Ultrasound images (US) are classified into two categories: Normal and abnormal. The abnormal subjects include hydrocephalus, microcephaly and dolichocephaly anomalies. By the use of a support vector machines (SVM) method, this study achieved high classification for automated detection of anomalies. The proposed method is promising although it doesn't need expert interventions.Keywords: biometric measurements, fetal head malformations, machine learning methods, US images
Procedia PDF Downloads 29215494 The Effects of in vitro Digestion on Cheese Bioactivity; Comparing Adult and Elderly Simulated in vitro Gastrointestinal Digestion Models
Authors: A. M. Plante, F. O’Halloran, A. L. McCarthy
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By 2050 it is projected that 2 billion of the global population will be more than 60 years old. Older adults have unique dietary requirements and aging is associated with physiological changes that affect appetite, sensory perception, metabolism, and digestion. Therefore, it is essential that foods recommended and designed for older adults promote healthy aging. To assess cheese as a functional food for the elderly, a range of commercial cheese products were selected and compared for their antioxidant properties. Cheese from various milk sources (bovine, goats, sheep) with different textures and fat content, including cheddar, feta, goats, brie, roquefort, halloumi, wensleydale and gouda, were initially digested with two different simulated in vitro gastrointestinal digestion (SGID) models. One SGID model represented a validated in vitro adult digestion system and the second model, an elderly SGID, was designed to consider the physiological changes associated with aging. The antioxidant potential of all cheese digestates was investigated using in vitro chemical-based antioxidant assays, (2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, ferric reducing antioxidant power (FRAP) and total phenolic content (TPC)). All adult model digestates had high antioxidant activity across both DPPH ( > 70%) and FRAP ( > 700 µM Fe²⁺/kg.fw) assays. Following in vitro digestion using the elderly SGID model, full-fat red cheddar, low-fat white cheddar, roquefort, halloumi, wensleydale, and gouda digestates had significantly lower (p ≤ 0.05) DPPH radical scavenging properties compared to the adult model digestates. Full-fat white cheddar had higher DPPH radical scavenging activity following elderly SGID digestion compared to the adult model digestate, but the difference was not significant. All other cheese digestates from the elderly model were comparable to the digestates from the adult model in terms of radical scavenging activity. The FRAP of all elderly digestates were significantly lower (p ≤ 0.05) compared to the adult digestates. Goats cheese was significantly higher (p ≤ 0.05) in FRAP (718 µM Fe²/kg.fw) compared to all other digestates in the elderly model. TPC levels in the soft cheeses (feta, goats) and low-fat cheeses (red cheddar, white cheddar) were significantly lower (p ≤ 0.05) in the elderly digestates compared to the adult digestates. There was no significant difference in TPC levels, between the elderly and adult model for full-fat cheddar (red, white), roquefort, wensleydale, gouda, and brie digestates. Halloumi cheese was the only cheese that was significantly higher in TPC levels following elderly digestion compared to adult digestates. Low fat red cheddar had significantly higher (p ≤ 0.05) TPC levels compared to all other digestates for both adult and elderly digestive systems. Findings from this study demonstrate that aging has an impact on the bioactivity of cheese, as antioxidant activity and TPC levels were lower, following in vitro elderly digestion compared to the adult model. For older adults, soft cheese, particularly goats cheese, was associated with high radical scavenging and reducing power, while roquefort cheese had low antioxidant activity. Also, elderly digestates of halloumi and low-fat red cheddar were associated with high TPC levels. Cheese has potential as a functional food for the elderly, however, bioactivity can vary depending on the cheese matrix. Funding for this research was provided by the RISAM Scholarship Scheme, Cork Institute of Technology, Ireland.Keywords: antioxidants, cheese, in-vitro digestion, older adults
Procedia PDF Downloads 23215493 A Neural Network Approach to Understanding Turbulent Jet Formations
Authors: Nurul Bin Ibrahim
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Advancements in neural networks have offered valuable insights into Fluid Dynamics, notably in addressing turbulence-related challenges. In this research, we introduce multiple applications of models of neural networks, namely Feed-Forward and Recurrent Neural Networks, to explore the relationship between jet formations and stratified turbulence within stochastically excited Boussinesq systems. Using machine learning tools like TensorFlow and PyTorch, the study has created models that effectively mimic and show the underlying features of the complex patterns of jet formation and stratified turbulence. These models do more than just help us understand these patterns; they also offer a faster way to solve problems in stochastic systems, improving upon traditional numerical techniques to solve stochastic differential equations such as the Euler-Maruyama method. In addition, the research includes a thorough comparison with the Statistical State Dynamics (SSD) approach, which is a well-established method for studying chaotic systems. This comparison helps evaluate how well neural networks can help us understand the complex relationship between jet formations and stratified turbulence. The results of this study underscore the potential of neural networks in computational physics and fluid dynamics, opening up new possibilities for more efficient and accurate simulations in these fields.Keywords: neural networks, machine learning, computational fluid dynamics, stochastic systems, simulation, stratified turbulence
Procedia PDF Downloads 7815492 The Analysis of the Effect of Brand Image on Creating Brand Loyalty with the Structural Equation Model: A Research Study on the Sports Equipment Brand Users
Authors: Murat Erdoğdu, Murat Koçyiğit
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Brand image and brand loyalty are among the most important relational marketing elements for brand owners to be able to set up long – term relationships with their customers and to maintain these relationships. Brand owners improve their brand images with the positive perceptions remaining in the consumers’ minds. In addition, they try to find the customers that are both emotionally and behaviourally faithful to themselves in order to set up long – term relationships. Therefore, the aim of this study is to analyse the effects of the brand image that has a very important role among relational marketing elements on the brand loyalty in terms of the variables such as the perceived value, the trust in brand and the brand satisfaction. In this context, a conceptual model was created to determine the effect of the brand image on the brand loyalty thanks to the Structural Equation Model (SEM). According to this aim and this model, the study was carried out in the scope of the data collected through the questionnaires in Konya with the method of convenience sampling. The results of the research showed that the brand image has positive significant effects on the perceived value and the trust in brand and that the trust in brand has positive significant effects on the brand satisfaction, and that the brand satisfaction has positive significant effects on the brand loyalty. Thus, the hypotheses that the brand image has direct effects on the perceived value and the trust in brand and that the trust in brand has direct effects on the brand satisfaction and that the brand satisfaction has direct effects on the brand loyalty were supported. In addition, the findings about whether the perceived value has a significant effect on the brand satisfaction were also acquired.Keywords: brand image, brand loyalty, perceived value, satisfaction, trust
Procedia PDF Downloads 44115491 Simulation of 1D Dielectric Barrier Discharge in Argon Mixtures
Authors: Lucas Wilman Crispim, Patrícia Hallack, Maikel Ballester
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This work aims at modeling electric discharges in gas mixtures. The mathematical model mimics the ignition process in a commercial spark-plug when a high voltage is applied to the plug terminals. A longitudinal unidimensional Cartesian domain is chosen for the simulation region. Energy and mass transfer are considered for a macroscopic fluid representation, while energy transfer in molecular collisions and chemical reactions are contemplated at microscopic level. The macroscopic model is represented by a set of uncoupled partial differential equations. Microscopic effects are studied within a discrete model for electronic and molecular collisions in the frame of ZDPlasKin, a plasma modeling numerical tool. The BOLSIG+ solver is employed in solving the electronic Boltzmann equation. An operator splitting technique is used to separate microscopic and macroscopic models. The simulation gas is a mixture of atomic Argon neutral, excited and ionized. Spatial and temporal evolution of such species and temperature are presented and discussed.Keywords: CFD, electronic discharge, ignition, spark plug
Procedia PDF Downloads 16515490 Alternating Expectation-Maximization Algorithm for a Bilinear Model in Isoform Quantification from RNA-Seq Data
Authors: Wenjiang Deng, Tian Mou, Yudi Pawitan, Trung Nghia Vu
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Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform reads distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide a bias correction step(s), which is based on biological considerations, such as GC content–and applied in single samples separately. The main problem is that not all biases are known. For example, new technologies such as single-cell RNA-seq (scRNA-seq) may introduce new sources of bias not seen in bulk-cell data. This study introduces a method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and derived based on the simplifying assumptions. In contrast, XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. XAEM implements an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to other recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes, particularly for paralogs. In a differential-expression analysis of a real scRNA-seq dataset, XAEM achieves substantially greater rediscovery rates in an independent validation set.Keywords: alternating EM algorithm, bias correction, bilinear model, gene expression, RNA-seq
Procedia PDF Downloads 14615489 On Consolidated Predictive Model of the Natural History of Breast Cancer Considering Primary Tumor and Primary Distant Metastases Growth
Authors: Ella Tyuryumina, Alexey Neznanov
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Finding algorithms to predict the growth of tumors has piqued the interest of researchers ever since the early days of cancer research. A number of studies were carried out as an attempt to obtain reliable data on the natural history of breast cancer growth. Mathematical modeling can play a very important role in the prognosis of tumor process of breast cancer. However, mathematical models describe primary tumor growth and metastases growth separately. Consequently, we propose a mathematical growth model for primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoM-IV and corresponding software. We are interested in: 1) modelling the whole natural history of primary tumor and primary metastases; 2) developing adequate and precise CoM-IV which reflects relations between PT and MTS; 3) analyzing the CoM-IV scope of application; 4) implementing the model as a software tool. The CoM-IV is based on exponential tumor growth model and consists of a system of determinate nonlinear and linear equations; corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and primary metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for primary metastases; 3) ‘visible period’ for primary metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of the period of primary metastases appearance; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of BC and facilitate optimization of diagnostic tests. The following are calculated by CoM-IV: the number of doublings for ‘nonvisible’ and ‘visible’ growth period of primary metastases; tumor volume doubling time (days) for ‘nonvisible’ and ‘visible’ growth period of primary metastases. The CoM-IV enables, for the first time, to predict the whole natural history of primary tumor and primary metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-IV describes correctly primary tumor and primary distant metastases growth of IV (T1-4N0-3M1) stage with (N1-3) or without regional metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and manifestation of primary metastases.Keywords: breast cancer, exponential growth model, mathematical modelling, primary metastases, primary tumor, survival
Procedia PDF Downloads 33715488 Hydrodynamic Analysis on the Body of a Solar Autonomous Underwater Vehicle by Numerical Method
Authors: Mohammad Moonesun, Ehsan Asadi Asrami, Julia Bodnarchuk
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In the case of Solar Autonomous Underwater Vehicle, which uses photovoltaic panels to provide its required power, due to limitation of energy, accurate estimation of resistance and energy has major sensitivity. In this work, hydrodynamic calculations by numerical method for a solar autonomous underwater vehicle equipped by two 50 W photovoltaic panels has been studied. To evaluate the required power and energy, hull hydrodynamic resistance in several velocities should be taken into account. To do this assessment, the ANSYS FLUENT 18 applied as Computational Fluid Dynamics (CFD) tool that solves Reynolds Average Navier Stokes (RANS) equations around AUV hull, and K-ω SST is used as turbulence model. To validate of solution method and modeling approach, the model of Myring submarine that it’s experimental data was available, is simulated. There is good agreement between numerical and experimental results. Also, these results showed that the K-ω SST Turbulence model is an ideal method to simulate the AUV motion in low velocities.Keywords: underwater vehicle, hydrodynamic resistance, numerical modelling, CFD, RANS
Procedia PDF Downloads 21115487 Mechanisms for the Art of Food: Tourism with Thainess and a Multi-Stakeholder Participation Approach
Authors: Jutamas Wisansing, Thanakarn Vongvisitsin, Udom Hongchatikul
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Food could be used to open up a dialogue about local heritage. Contributing to the world sustainable consumption mission, this research aims to explore the linkages between agriculture, senses of place and performing arts. Thailand and its destination marketing ‘Discover Thainess’ was selected as a working principle, enabling a case example of how the three elements could be conceptualized. The model offered an integrated institutional arrangement where diverse entities could be formed to design how Thainess (local heritage) could be interpreted and embedded into an art of food. Using case study research approach, three areas (Chiangmai, Samutsongkram and Ban Rai Gong King) representing 3 different scales of tourism development were selected. Based on a theoretical analysis, a working model was formulated. An action research was then designed to experiment how the model could be materialized. Brainstorming elicitation and in-depth interview were employed to reflect on how each element could be integrated. The result of this study offered an innovation on how food tourism could be profoundly interpreted and how tourism development could enhance value creation for agricultural based community. The outcomes of the research present co-creative multi-stakeholder model and the value creation method through the whole supply chain of Thai gastronomy. The findings have been eventually incorporated into ‘gastro-diplomacy’ strategy for Thai tourism.Keywords: community-based tourism, gastro-diplomacy, gastronomy tourism, sustainable tourism development
Procedia PDF Downloads 31315486 Temporal Migration and Community Development in Rural Indonesia
Authors: Gunawan Prayitno, Kakuya Matshusima, Kiyoshi Kobayashi
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Indonesia’s rural regions are characterized by wide-spread poverty, under-employment, and surplus of low-skilled labor. The aim of this paper is to empirically prove the effect of social ties (strong and weak tie) as social capital construct on households’ migration decision in the case of developing country (Indonesia). The methodology incorporated indicators of observe variables (four demographic attributes data: income, occupation, education, and family members) and indicators of latent variables (ties to neighbors, ties to community and sense of place) provided by responses to survey questions to aid in estimating the model. Using structural equation model that we employed in Mplus program, the result of our study shows that ties to community positively have a significant impact to the decision of respondents (migrate or not). Besides, education as observed variable directly influences the migration decisions. It seems that higher level of education have impact on migration decision. Our current model so far could explain the relation between social capital and migration decision choice.Keywords: migration, ties to community, ties to neighbors, education
Procedia PDF Downloads 32715485 An Efficient Hybrid Feedstock Pretreatment Technique for the Release of Fermentable Sugar from Cassava Peels for Biofuel Production
Authors: Gabriel Sanjo Aruwajoye, E. B. Gueguim Kana
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Agricultural residues present a low-cost feedstock for bioenergy production around the world. Cassava peels waste are rich in organic molecules that can be readily converted to value added products such as biomaterials and biofuels. However, due to the presence of high proportion of structural carbohydrates and lignin, the hydrolysis of this feedstock is imperative to achieve maximum substrate utilization and energy yield. This study model and optimises the release of Fermentable Sugar (FS) from cassava peels waste using the Response Surface Methodology. The investigated pretreatment input parameters consisted of soaking temperature (oC), soaking time (hours), autoclave duration (minutes), acid concentration (% v/v), substrate solid loading (% w/v) within the range of 30 to 70, 0 to 24, 5 to 20, 0 to 5 and 2 to 10 respectively. The Box-Behnken design was used to generate 46 experimental runs which were investigated for FS release. The obtained data were used to fit a quadratic model. A coefficient of determination of 0.87 and F value of 8.73 was obtained indicating the good fitness of the model. The predicted optimum pretreatment conditions were 69.62 oC soaking temperature, 2.57 hours soaking duration, 5 minutes autoclave duration, 3.68 % v/v HCl and 9.65 % w/v solid loading corresponding to FS yield of 91.83g/l (0.92 g/g cassava peels) thus 58% improvement on the non-optimised pretreatment. Our findings demonstrate an efficient pretreatment model for fermentable sugar release from cassava peels waste for various bioprocesses.Keywords: feedstock pretreatment, cassava peels, fermentable sugar, response surface methodology
Procedia PDF Downloads 37215484 Academia as Creator of Emerging, Innovative Communities of Practice and Learning
Authors: Francisco Julio Batle Lorente
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The present paper aims at presenting a new category of role for academia: proactive creator/promoter of communities of practice in emerging areas of innovation. It is based in research among practitioners in three different areas: social entrepreneurship, alumni engaged in entrepreneurship and innovation, and digital nomads. The concept of CoP is related to an intentionally created space to share experiences and collectively reflect on the cases arising from practice. Such an endeavour is not contemplated in the literature on academic roles in an explicit way. The goal of the paper is providing a framework for this function and throw some light on the perception and priorities of members of emerging communities (78 alumni, 154 social entrepreneurs, and 231 digital nomads) regarding community, learning, engagement, and networking, areas in which the university can help and, by doing so, contributing to signal the emerging area and creating new opportunities for the academia. The research methodology was based in Survey research. It is a specific type of field study that involves the collection of data from a sample of elements drawn from a well-defined population through the use of a questionnaire. It was considered that survey research might be valuable to the present project and help outline the utility of various study designs and future projects with the emerging communities that are the object of the investigation. Open questions were used for different topics, as well as critical incident technique. It was used a standard technique for survey sampling and questionnaire design. Finally, it was defined a procedure for pretesting questionnaires and for data collection. The questionnaire was channelled by means of google forms. The results indicate that the members of emerging, innovative CoPs and learning such the ones that were selected for this investigation lack cohesion, inspiration, networking, opportunities for creation of social capital, opportunities for collaboration beyond their existing and close network. The opportunity that arises for the academia from proactively helping articulate CoP (and Communities of learning) are related to key elements of any CoP/ CoL: community construction approaches, technological infrastructure, benefits, participation issues and urgent challenges, trust, networking, technical ability/training/development and collaboration. Beyond training, other three areas (networking, collaboration and urgent challenges) were the ones in which the contribution of universities to the communities were considered more interesting and workable to practitioners. The analysis of the responses for the open questions related to perception of the universities offer options for terra incognita to be explored for universities (signalling new areas, establishing broader collaborations with research, government, media and corporations, attracting investment). Based on the findings from this research, there is some evidence that CoPs can offer a formal and informal method of professional and interprofessional development for member of any emerging and innovative community and can decrease social and professional isolation. The opportunity that it offers to academia can increase the entrepreneurial and engaged university identity. It also moves to academia into a realm of civic confrontation of present and future challenges in a more proactive way.Keywords: social innovation, new roles of academia, community of learning, community of practice
Procedia PDF Downloads 8615483 Automation of AAA Game Development Using AI
Authors: Branden Heng, Harsheni Siddharthan, Allison Tseng, Paul Toprac, Sarah Abraham, Etienne Vouga
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The goal of this project was to evaluate and document the capabilities and limitations of AI tools for empowering small teams to create high-budget, high-profile (AAA) 3D games typically developed by large studios. Two teams of novice game developers attempted to create two different games using AI and Unreal Engine 5.3. First, the teams evaluated 60 AI art, design, sound, and programming tools by considering their capability, ease of use, cost, and license restrictions. Then, the teams used a shortlist of 12 AI tools for game development. During this process, the following tools were found to be the most productive: (i) ChatGPT 4.0 for both game and narrative concepts and documentation; (ii) Dall-E 3 and OpenArt for concept art; (iii) Beatoven for music drafting; (iv) ChatGPT 4.0 and Github Copilot for generating simple code and to complement human-made tutorials as an additional learning resource. While current generative AI may appear impressive at first glance, the assets they produce fall short of AAA industry standards. Generative AI tools are helpful when brainstorming ideas such as concept art and basic storylines, but they still cannot replace human input or creativity at this time. Regarding programming, AI can only effectively generate simple code and act as an additional learning resource. Thus, generative AI tools are, at best, tools to enhance developer productivity rather than as a system to replace developers.Keywords: AAA games, AI, automation tools, game development
Procedia PDF Downloads 3115482 Fourier Transform and Machine Learning Techniques for Fault Detection and Diagnosis of Induction Motors
Authors: Duc V. Nguyen
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Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest benet based on their requirements. These are the key requirements of a robust prognostics and health management system.Keywords: fault detection, FFT, induction motor, predictive maintenance
Procedia PDF Downloads 17915481 Determinants of Smallholder Farmers' Intention to Adopt Jatropha as Raw Material for Biodiesel Production: A Proposed Model for Nigeria
Authors: Abdulsalam Mas’ud
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Though Nigerian Biofuel Policy and Incentive was introduced in 2007, however, little if any is known about the impact of such policy for biodiesel development in Nigeria. It can be argued that lack of raw materials is one of the important factors that hinder the proper implementation of the policy. In line with this argument, this study aims to explore the determinants of smallholder farmers’ intention to adopt Jatropha as raw materials for biodiesel development in northern Nigeria, with Jigawa State as area of study. The determinants proposed for investigation covers personal factors, physical factors, institutional factors, economic factors, risk and uncertainty factors as well as social factors. The validation of the proposed model will have the implication of guiding policymakers towards enhancement of farmers’ participation in the Jatropha project for biodiesel raw materials production. The eventual byproducts of the proposed model validation and implementation will be employment generation, poverty reduction, combating dessert encroachment, economic diversification to renewable energy sources and electricity generation.Keywords: adoption, biodiesel, factors, jatropha
Procedia PDF Downloads 31315480 Study of Morning-Glory Spillway Structure in Hydraulic Characteristics by CFD Model
Authors: Mostafa Zandi, Ramin Mansouri
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Spillways are one of the most important hydraulic structures of dams that provide the stability of the dam and downstream areas at the time of flood. Morning-Glory spillway is one of the common spillways for discharging the overflow water behind dams, these kinds of spillways are constructed in dams with small reservoirs. In this research, the hydraulic flow characteristics of a morning-glory spillways are investigated with CFD model. Two dimensional unsteady RANS equations were solved numerically using Finite Volume Method. The PISO scheme was applied for the velocity-pressure coupling. The mostly used two-equation turbulence models, k- and k-, were chosen to model Reynolds shear stress term. The power law scheme was used for discretization of momentum, k , and equations. The VOF method (geometrically reconstruction algorithm) was adopted for interface simulation. The results show that the fine computational grid, the input speed condition for the flow input boundary, and the output pressure for the boundaries that are in contact with the air provide the best possible results. Also, the standard wall function is chosen for the effect of the wall function, and the turbulent model k -ε (Standard) has the most consistent results with experimental results. When the jet is getting closer to end of basin, the computational results increase with the numerical results of their differences. The lower profile of the water jet has less sensitivity to the hydraulic jet profile than the hydraulic jet profile. In the pressure test, it was also found that the results show that the numerical values of the pressure in the lower landing number differ greatly in experimental results. The characteristics of the complex flows over a Morning-Glory spillway were studied numerically using a RANS solver. Grid study showed that numerical results of a 57512-node grid had the best agreement with the experimental values. The desired downstream channel length was preferred to be 1.5 meter, and the standard k-ε turbulence model produced the best results in Morning-Glory spillway. The numerical free-surface profiles followed the theoretical equations very well.Keywords: morning-glory spillway, CFD model, hydraulic characteristics, wall function
Procedia PDF Downloads 8015479 Comparative Study of the Earth Land Surface Temperature Signatures over Ota, South-West Nigeria
Authors: Moses E. Emetere, M. L. Akinyemi
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Agricultural activities in the South–West Nigeria are mitigated by the global increase in temperature. The unpredictive surface temperature of the area had increased health challenges amongst other social influence. The satellite data of surface temperatures were compared with the ground station Davis weather station. The differential heating of the lower atmosphere were represented mathematically. A numerical predictive model was propounded to forecast future surface temperature.Keywords: numerical predictive model, surface temperature, satellite date, ground data
Procedia PDF Downloads 47615478 Error Analysis: Examining Written Errors of English as a Second Language (ESL) Spanish Speaking Learners
Authors: Maria Torres
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After the acknowledgment of contrastive analysis, Pit Coder’s establishment of error analysis revolutionized the way instructors analyze and examine students’ writing errors. One question that relates to error analysis with speakers of a first language, in this case, Spanish, who are learning a second language (English), is the type of errors that these learners make along with the causes of these errors. Many studies have looked at the way the native tongue influences second language acquisition, but this method does not take into account other possible sources of students’ errors. This paper examines writing samples from an advanced ESL class whose first language is Spanish at non-profit organization, Learning Quest Stanislaus Literacy Center. Through error analysis, errors in the students’ writing were identified, described, and classified. The purpose of this paper was to discover the type and origin of their errors which generated appropriate treatments. The results in this paper show that the most frequent errors in the advanced ESL students’ writing pertain to interlanguage and a small percentage from an intralanguage source. Lastly, the least type of errors were ones that originate from negative transfer. The results further solidify the idea that there are other errors and sources of errors to account for rather than solely focusing on the difference between the students’ mother and target language. This presentation will bring to light some strategies and techniques that address the issues found in this research. Taking into account the amount of error pertaining to interlanguage, an ESL teacher should provide metalinguistic awareness of the students’ errors.Keywords: error analysis, ESL, interlanguage, intralangauge
Procedia PDF Downloads 30015477 Systems Intelligence in Management (High Performing Organizations and People Score High in Systems Intelligence)
Authors: Raimo P. Hämäläinen, Juha Törmänen, Esa Saarinen
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Systems thinking has been acknowledged as an important approach in the strategy and management literature ever since the seminal works of Ackhoff in the 1970´s and Senge in the 1990´s. The early literature was very much focused on structures and organizational dynamics. Understanding systems is important but making improvements also needs ways to understand human behavior in systems. Peter Senge´s book The Fifth Discipline gave the inspiration to the development of the concept of Systems Intelligence. The concept integrates the concepts of personal mastery and systems thinking. SI refers to intelligent behavior in the context of complex systems involving interaction and feedback. It is a competence related to the skills needed in strategy and the environment of modern industrial engineering and management where people skills and systems are in an increasingly important role. The eight factors of Systems Intelligence have been identified from extensive surveys and the factors relate to perceiving, attitude, thinking and acting. The personal self-evaluation test developed consists of 32 items which can also be applied in a peer evaluation mode. The concept and test extend to organizations too. One can talk about organizational systems intelligence. This paper reports the results of an extensive survey based on peer evaluation. The results show that systems intelligence correlates positively with professional performance. People in a managerial role score higher in SI than others. Age improves the SI score but there is no gender difference. Top organizations score higher in all SI factors than lower ranked ones. The SI-tests can also be used as leadership and management development tools helping self-reflection and learning. Finding ways of enhancing learning organizational development is important. Today gamification is a new promising approach. The items in the SI test have been used to develop an interactive card game following the Topaasia game approach. It is an easy way of engaging people in a process which both helps participants see and approach problems in their organization. It also helps individuals in identifying challenges in their own behavior and in improving in their SI.Keywords: gamification, management competence, organizational learning, systems thinking
Procedia PDF Downloads 10115476 Cloud Enterprise Application Provider Selection Model for the Small and Medium Enterprise: A Pilot Study
Authors: Rowland R. Ogunrinde, Yusmadi Y. Jusoh, Noraini Che Pa, Wan Nurhayati W. Rahman, Azizol B. Abdullah
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Enterprise Applications (EAs) aid the organizations achieve operational excellence and competitive advantage. Over time, most Small and Medium Enterprises (SMEs), which are known to be the major drivers of most thriving global economies, use the costly on-premise versions of these applications thereby making business difficult to competitively thrive in the same market environment with their large enterprise counterparts. The advent of cloud computing presents the SMEs an affordable offer and great opportunities as such EAs can be cloud-hosted and rented on a pay-per-use basis which does not require huge initial capital. However, as there are numerous Cloud Service Providers (CSPs) offering EAs as Software-as-a-Service (SaaS), there is a challenge of choosing a suitable provider with Quality of Service (QoS) that meet the organizations’ customized requirements. The proposed model takes care of that and goes a step further to select the most affordable among a selected few of the CSPs. In the earlier stage, before developing the instrument and conducting the pilot test, the researchers conducted a structured interview with three experts to validate the proposed model. In conclusion, the validity and reliability of the instrument were tested through experts, typical respondents, and analyzed with SPSS 22. Results confirmed the validity of the proposed model and the validity and reliability of the instrument.Keywords: cloud service provider, enterprise application, quality of service, selection criteria, small and medium enterprise
Procedia PDF Downloads 18015475 A Proposal for Professional Development of Mathematics Teachers in the Kingdom of Saudi Arabia According to the Orientation of Science, Technology, Engineering and Mathematics (STEM)
Authors: Ali Taher Othman Ali
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The aim of this research is to provide a draft proposal for the professional development of mathematics teachers in accordance with the orientation of science, technology, engineering and mathematics which is known by the abbreviation STEM, as a modern and contemporary orientation in the teaching and learning of mathematics and in order to achieve the objective of the research, the researcher used the theoretical descriptive method through the induction of the literature of education and the previous studies and experiments related to the topic. The researcher concluded by providing the proposal according to five basic axes, the first axe: professional development as a system, and its requirements include: development of educational systems, and allocate sufficient budgets to support the requirements of teaching STEM, identifying mechanisms for incentives and rewards for teachers attending professional development programs based on STEM; the second: development of in-depth knowledge content and its requirements include: basic sciences content development for STEM, linking the scientific understanding of teachers with real-world issues and problems, to provide the necessary resources to expand teachers' knowledge in this area; the third: the necessary pedagogical skills of teachers in the field of STEM, and its requirements include: identification of the required training and development needs and the mechanism of determining these needs, the types of professional development programs and the mechanism of designing it, the mechanisms and places of execution, evaluation and follow-up; the fourth: professional development strategies and mechanisms in the field of STEM, and its requirements include: using a variety of strategies to enable teachers to design and transfer effective educational experiences which reflect their scientific mastery in the fields of STEM, provide learning opportunities, and developing the skills of procedural research to generate new knowledge about the STEM; the fifth: to support professional development in the area of STEM, and its requirements include: support leadership within the school, provide a clear and appropriate opportunities for professional development for teachers within the school through professional learning communities, building partnerships between the Ministry of education and the local and international community institutions. The proposal includes other factors that should be considered when implementing professional development programs for mathematics teachers in the field of STEM.Keywords: professional development, mathematics teachers, the orientation of science, technology, engineering and mathematics (STEM)
Procedia PDF Downloads 41215474 Grey Wolf Optimization Technique for Predictive Analysis of Products in E-Commerce: An Adaptive Approach
Authors: Shital Suresh Borse, Vijayalaxmi Kadroli
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E-commerce industries nowadays implement the latest AI, ML Techniques to improve their own performance and prediction accuracy. This helps to gain a huge profit from the online market. Ant Colony Optimization, Genetic algorithm, Particle Swarm Optimization, Neural Network & GWO help many e-commerce industries for up-gradation of their predictive performance. These algorithms are providing optimum results in various applications, such as stock price prediction, prediction of drug-target interaction & user ratings of similar products in e-commerce sites, etc. In this study, customer reviews will play an important role in prediction analysis. People showing much interest in buying a lot of services& products suggested by other customers. This ultimately increases net profit. In this work, a convolution neural network (CNN) is proposed which further is useful to optimize the prediction accuracy of an e-commerce website. This method shows that CNN is used to optimize hyperparameters of GWO algorithm using an appropriate coding scheme. Accurate model results are verified by comparing them to PSO results whose hyperparameters have been optimized by CNN in Amazon's customer review dataset. Here, experimental outcome proves that this proposed system using the GWO algorithm achieves superior execution in terms of accuracy, precision, recovery, etc. in prediction analysis compared to the existing systems.Keywords: prediction analysis, e-commerce, machine learning, grey wolf optimization, particle swarm optimization, CNN
Procedia PDF Downloads 11815473 Innovative Tool for Improving Teaching and Learning
Authors: Izharul Haq
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Every one of us seek to aspire to gain quality education. The biggest stake holders are students who labor through years acquiring knowledge and skill to help them prepare for their career. Parents spend a fortune on their children’s education. Companies spend billions of dollars to enhance standards by developing new education products and services. Quality education is the golden key to a long lasting prosperity for the individual and the nation. But unfortunately, education standards are continuously deteriorating and it has become a global phenomenon. Unfortunately, teaching is often described as a ‘popularity contest’ and those teachers who are usually popular with students are often those who compromise teaching to appease students. Such teachers also ‘teach-to-the-test’ ensuring high test scores. Such teachers, hence, receive good student rating. Teachers who are conscientious, rigorous and thorough are often the victims of good appraisal. Government and private organizations are spending billions of dollars trying to capture the characteristics of a good teacher. But the results are still vague and inconclusive. At present there is no objective way to measure teaching effectiveness. In this paper we present an innovative method to objectively measure teaching effectiveness using a new teaching tool (TSquare). The TSquare tool used in the study is practical, easy to use, cost effective and requires no special equipment to implement. Hence it has a global appeal for poor and the rich countries alike.Keywords: measuring teaching effectiveness, quality in education, student learning, teaching styles
Procedia PDF Downloads 30115472 Citizens’ Readiness to Adopt and Use Electronic Voting System in Ghana
Authors: Isaac Kofi Mensah
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The adoption and application of Information and Communication Technologies (ICTs) in government administration through e-government is expected to permeate all sectors of state/ public institutions as well as democratic institutions. One of such public institutions is the Electoral Commission of Ghana mandated by the 1992 Constitution to hold all public elections including presidential and parliamentary elections. As Ghana holds its 7th General Elections since 1992, on 7th November 2016, there are demands from key stakeholders for the Election Management Body, which is the Electoral Commission (EC) of Ghana to adopt and implement an electronic voting system. This case study, therefore, attempts to contribute significantly to the debate by examining influencing factors that would impact on citizen’s readiness to adopt and use an electronic voting system in Ghana. The Technology Acceptance Model (TAM) was used as a theoretical framework for this study, out of which a research model and hypotheses were developed. Importantly, the outcome of this research finding would form a basis for appropriate policy recommendation for consideration of Government and EC of Ghana.Keywords: citizens readiness, e-government, electronic voting, technology acceptance model (TAM)
Procedia PDF Downloads 27315471 Cognitive Behavioral Modification in the Treatment of Aggressive Behavior in Children
Authors: Dijana Sulejmanović
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Cognitive-behavioral modification (CBM) is a combination of cognitive and behavioral learning principles to shape and encourage the desired behaviors. A crucial element of cognitive-behavioral modification is that a change the behavior precedes awareness of how it affects others. CBM is oriented toward changing inner speech and learning to control behaviors through self-regulation techniques. It aims to teach individuals how to develop the ability to recognize, monitor and modify their thoughts, feelings, and behaviors. The review of literature emphasizes the efficiency the CBM approach in the treatment of children's hyperactivity and negative emotions such as anger. The results of earlier research show how impulsive and hyperactive behavior, agitation, and aggression may slow down and block the child from being able to actively monitor and participate in regular classes, resulting in the disruption of the classroom and the teaching process, and the children may feel rejected, isolated and develop long-term poor image of themselves and others. In this article, we will provide how the use of CBM, adapted to child's age, can incorporate measures of cognitive and emotional functioning which can help us to better understand the children’s cognitive processes, their cognitive strengths, and weaknesses, and to identify factors that may influence their behavioral and emotional regulation. Such a comprehensive evaluation can also help identify cognitive and emotional risk factors associated with aggressive behavior, specifically the processes involved in modulating and regulating cognition and emotions.Keywords: aggressive behavior, cognitive behavioral modification, cognitive behavioral theory, modification
Procedia PDF Downloads 33215470 A Study on the Influence of Pin-Hole Position Error of Carrier on Mesh Load and Planet Load Sharing of Planetary Gear
Authors: Kyung Min Kang, Peng Mou, Dong Xiang, Gang Shen
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For planetary gear system, Planet pin-hole position accuracy is one of most influential factor to efficiency and reliability of planetary gear system. This study considers planet pin-hole position error as a main input error for model and build multi body dynamic simulation model of planetary gear including planet pin-hole position error using MSC. ADAMS. From this model, the mesh load results between meshing gears in each pin-hole position error cases are obtained and based on these results, planet load sharing factor which reflect equilibrium state of mesh load sharing between whole meshing gear pair is calculated. Analysis result indicates that the pin-hole position error of tangential direction cause profound influence to mesh load and load sharing factor between meshing gear pair.Keywords: planetary gear, load sharing factor, multibody dynamics, pin-hole position error
Procedia PDF Downloads 58615469 Fast and Accurate Model to Detect Ictal Waveforms in Electroencephalogram Signals
Authors: Piyush Swami, Bijaya Ketan Panigrahi, Sneh Anand, Manvir Bhatia, Tapan Gandhi
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Visual inspection of electroencephalogram (EEG) signals to detect epileptic signals is very challenging and time-consuming task even for any expert neurophysiologist. This problem is most challenging in under-developed and developing countries due to shortage of skilled neurophysiologists. In the past, notable research efforts have gone in trying to automate the seizure detection process. However, due to high false alarm detections and complexity of the models developed so far, have vastly delimited their practical implementation. In this paper, we present a novel scheme for epileptic seizure detection using empirical mode decomposition technique. The intrinsic mode functions obtained were then used to calculate the standard deviations. This was followed by probability density based classifier to discriminate between non-ictal and ictal patterns in EEG signals. The model presented here demonstrated very high classification rates ( > 97%) without compromising the statistical performance. The computation timings for each testing phase were also very low ( < 0.029 s) which makes this model ideal for practical applications.Keywords: electroencephalogram (EEG), epilepsy, ictal patterns, empirical mode decomposition
Procedia PDF Downloads 41115468 Feasibility of Using Bike Lanes in Conjunctions with Sidewalks for Ground Drone Applications in Last Mile Delivery for Dense Urban Areas
Authors: N. Bazyar Shourabi, K. Nyarko, C. Scott, M. Jeihnai
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Ground drones have the potential to reduce the cost and time of making last-mile deliveries. They also have the potential to make a huge impact on human life. Despite this potential, little work has gone into developing a suitable feasibility model for ground drone delivery in dense urban areas. Today, most of the experimental ground delivery drones utilize sidewalks only, with just a few of them starting to use bike lanes, which a significant portion of some urban areas have. This study works on the feasibility of using bike lanes in conjunction with sidewalks for ground drone applications in last-mile delivery for dense urban areas. This work begins with surveying bike lanes and sidewalks within the city of Boston using Geographic Information System (GIS) software to determine the percentage of coverage currently available within the city. Then six scenarios are examined. Based on this research, a mathematical model is developed. The daily cost of delivering packages using each scenario is calculated by the mathematical model. Comparing the drone delivery scenarios with the traditional method of package delivery using trucks will provide essential information concerning the feasibility of implementing routing protocols that combine the use of sidewalks and bike lanes. The preliminary results of the model show that ground drones that can travel via sidewalks or bike lanes have the potential to significantly reduce delivery cost.Keywords: ground drone, intelligent transportation system, last-mile delivery, sidewalk robot
Procedia PDF Downloads 151