Search results for: learning satisfaction
4001 Teaching Gender and Language in the EFL Classroom in the Arab World: Algerian Students’ Awareness of Their Gender Identities from New Perspectives
Authors: Amina Babou
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Gender and language is a moot and miscellaneous arena in the sphere of sociolinguistics, which has been proliferated so widely and rapidly in recent years. The dawn of research on gender and foreign language education was against the feminist researchers who allowed space for the bustling concourse of voices and perspectives in the arena of gender and language differences, in the early to the mid-1970. The objective of this scrutiny is to explore to what extent teaching gender and language in the English as a Foreign Language (EFL) classroom plays a pivotal role in learning language information and skills. And the gist of this paper is to investigate how EFL students in Algeria conflate their gender identities with the linguistic practices and scholastic expertise. To grapple with the full range of issues about the EFL students’ awareness about the negotiation of meanings in the classroom, we opt for observing, interviewing, and questioning later to check using ‘how-do-you do’ procedure. The analysis of the EFL classroom discourse, from five Algerian universities, reveals that speaking strategies such as the manners students make an abrupt topic shifts, respond spontaneously to the teacher, ask more questions, interrupt others to seize control of conversations and monopolize the speaking floor through denying what others have said, do not sit very lightly on 80.4% of female students’ shoulders. The data indicate that female students display the assertive style as a strategy of learning to subvert the norms of femininity, especially in the speaking module.Keywords: gender identities, EFL students, classroom discourse, linguistics
Procedia PDF Downloads 4114000 Remote Sensing Approach to Predict the Impacts of Land Use/Land Cover Change on Urban Thermal Comfort Using Machine Learning Algorithms
Authors: Ahmad E. Aldousaria, Abdulla Al Kafy
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Urbanization is an incessant process that involves the transformation of land use/land cover (LULC), resulting in a reduction of cool land covers and thermal comfort zones (TCZs). This study explores the directional shrinkage of TCZs in Kuwait using Landsat satellite data from 1991 – 2021 to predict the future LULC and TCZ distribution for 2026 and 2031 using cellular automata (CA) and artificial neural network (ANN) algorithms. Analysis revealed a rapid urban expansion (40 %) in SE, NE, and NW directions and TCZ shrinkage in N – NW and SW directions with 25 % of the very uncomfortable area. The predicted result showed an urban area increase from 44 % in 2021 to 47 % and 52 % in 2026 and 2031, respectively, where uncomfortable zones were found to be concentrated around urban areas and bare lands in N – NE and N – NW directions. This study proposes an effective and sustainable framework to control TCZ shrinkage, including zero soil policies, planned landscape design, manmade water bodies, and rooftop gardens. This study will help urban planners and policymakers to make Kuwait an eco–friendly, functional, and sustainable country.Keywords: land cover change, thermal environment, green cover loss, machine learning, remote sensing
Procedia PDF Downloads 2273999 Keypoints Extraction for Markerless Tracking in Augmented Reality Applications: A Case Study in Dar As-Saraya Museum
Authors: Jafar W. Al-Badarneh, Abdalkareem R. Al-Hawary, Abdulmalik M. Morghem, Mostafa Z. Ali, Rami S. Al-Gharaibeh
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Archeological heritage is at the heart of each country’s national glory. Moreover, it could develop into a source of national income. Heritage management requires socially-responsible marketing that achieves high visitor satisfaction while maintaining high site conservation. We have developed an Augmented Reality (AR) experience for heritage and cultural reservation at Dar-As-Saraya museum in Jordan. Our application of this notion relied on markerless-based tracking approach. This approach uses keypoints extraction technique where features of the environment are identified and defined into the system as keypoints. A set of these keypoints forms a tracker for an augmented object to be displayed and overlaid with a real scene at Dar As-Saraya museum. We tested and compared several techniques for markerless tracking and then applied the best technique to complete a mosaic artifact with AR content. The successful results from our application open the door for applications in open archeological sites where markerless tracking is mostly needed.Keywords: augmented reality, cultural heritage, keypoints extraction, virtual recreation
Procedia PDF Downloads 3373998 Individuals’ Inner Wellbeing during the COVID-19 Pandemic: A Quantitative Comparison of Social Connections and Close Relationships between the UK and India
Authors: Maria Spanoudaki, Pauldy C. J. Otermans, Dev Aditya
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Relationships form an integral part of our everyday wellbeing. In this study, the focus is on Inner Wellbeing which can be described as an individuals' thoughts and feelings about what they can do and be. Relationships can come in many forms and can be divided into Social Connections (thoughts and feelings about the social network people can establish and rely on), and Close Relationships (thoughts and feeling about the emotional support people can receive from significant others or their close, intimate circle). The purpose of this study is to compare the Social Connections and Close Relationship dimensions of Inner Wellbeing during the COVID-19 pandemic between the UK and India. 392 participants in the UK and 205 participants India completed an online questionnaire using the Inner Wellbeing scale. Factor analyses showed that the construct of Inner Wellbeing can be described as one factor for the UK sample whereas it can be described as two factors (one focusing on positive items and one focusing on negative items) for the Indian sample. Results showed that Social Connections were significantly during COVID-19 in the UK compared to India, whereas there is no significant difference for Close Relationships. The implications on relationships and wellbeing are discussed in detail.Keywords: social networks, relationship maintenance, relationship satisfaction, COVID-19
Procedia PDF Downloads 1623997 Research on Resilience-Oriented Disintegration in System-of-System
Authors: Hang Yang, Jiahao Liu, Jichao Li, Kewei Yang, Minghao Li, Bingfeng Ge
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The system-of-systems (SoS) are utilized to characterize networks formed by integrating individual complex systems that demonstrate interdependence and interconnectedness. Research on the disintegration issue in SoS is significant in improving network survivability, maintaining network security, and optimizing SoS architecture. Accordingly, this study proposes an integrated framework called resilience-oriented disintegration in SoS (SoSRD), for modeling and solving the issue of SoS disintegration. Firstly, a SoS disintegration index (SoSDI) is presented to evaluate the disintegration effect of SoS. This index provides a practical description of the disintegration process and is the first integration of the network disintegration model and resilience models. Subsequently, we propose a resilience-oriented disintegration method based on reinforcement learning (RDRL) to enhance the efficiency of SoS disintegration. This method is not restricted by the problem scenario as well as considering the coexistence of disintegration (node/link removal) and recovery (node/link addition) during the process of SoS disintegration. Finally, the effectiveness and superiority of the proposed SoSRD are demonstrated through a case study. We demonstrate that our proposed framework outperforms existing indexes and methods in both node and link disintegration scenarios, providing a fresh perspective on network disintegration. The findings provide crucial insights into dismantling harmful SoS and designing a more resilient SoS.Keywords: system-of-systems, disintegration index, resilience, reinforcement learning
Procedia PDF Downloads 153996 The Impact of Corporate Social Responsibility on Tertiary Institutions in Bauchi State Nigeria
Authors: Aliyu Aminu Baba, Mustapha Makama
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Tertiary institutions are citadel of learning and societal orientation. Due to the huge investment of various government to tertiary institutions, these institutions are solely financed by the government alone. As stakeholders of society, corporations have to have to intervene and provide corporate social responsibility. The study intends to investigate the role of Entrepreneurs in incorporating social Responsibility. Tertiary institutions are citadel of learning and societal orientation. Due to the huge investment of various government to tertiary institutions, the study intends to investigate the role of businesses and Entrepreneurs, which could be among the important contributions of businesses and Entrepreneurs on corporate social Responsibility to Tertiary Institutions in Bauchi State. Corporate social responsibility is vital in enhancing the infrastructural development of the tertiary institution as almost all individuals and corporate bodies benefit from this tertiary institutions. The study intends to examine the impact of corporate social responsibility to tertiary institutions and entrepreneurs in Bauchi state Nigeria. Questionnaires would be distributed to tertiary institutions and entrepreneurs in the Bauchi metropolis. The data collected will be analyzed with the help of SPSS version 23. The main objective is to investigate the role of businesses and Entrepreneurs, which could be among the important contributions of businesses and entrepreneurs on corporate social Responsibility to Tertiary Institutions in Bauchi State.Keywords: corporate social responsibility, tertiary, institutions, profitability
Procedia PDF Downloads 2243995 The Impact of Perception of Transformational Leadership and Factors of Innovation Culture on Innovative Work Behavior in Junior High School's Teacher
Authors: Galih Mediana
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Boarding school can helps students to turn all good qualities into habits. The process of forming one's personality can be done in various ways. In addition to gaining general knowledge at school during learning hours, teachers can instill values in students which can be done while in the dormitory when the learning process has ended. This shows the important role that must be played by boarding school’s teachers. Transformational leadership and a culture of innovation are things that can instill innovative behavior in teachers. This study aims to determine the effect of perceptions of transformational leadership and a culture of innovation on innovative work behavior among Islamic boarding school teachers. Respondents in this study amounted to 70 teachers. To measure transformational leadership, a modified measuring tool is used, namely the Multifactor Leadership Questionnaire (MLQ) by Bass (1985). To measure innovative work behavior, a measurement tool based on dimensions from Janssen (2000) is used. The innovation culture in this study will be measured using the innovation culture factor from Dobni (2008). This study uses multiple regression analysis to test the hypothesis. The results of this study indicate that there is an influence of perceptions of transformational leadership and innovation culture factors on innovative work behavior in Islamic boarding school’s teachers by 57.7%.Keywords: transformational leadership, innovative work behavior, innovation culture, boarding school, teacher
Procedia PDF Downloads 1083994 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 3253993 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 4053992 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 2883991 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 703990 Anomaly Detection in a Data Center with a Reconstruction Method Using a Multi-Autoencoders Model
Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin
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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.Keywords: anomaly detection, autoencoder, data centers, deep learning
Procedia PDF Downloads 1943989 Impact of Primary Care Telemedicine Consultations On Health Care Resource Utilisation: A Systematic Review
Authors: Anastasia Constantinou, Stephen Morris
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Background: The adoption of synchronous and asynchronous telemedicine modalities for primary care consultations has exponentially increased since the COVID-19 pandemic. However, there is limited understanding of how virtual consultations influence healthcare resource utilization and other quality measures including safety, timeliness, efficiency, patient and provider satisfaction, cost-effectiveness and environmental impact. Aim: Quantify the rate of follow-up visits, emergency department visits, hospitalizations, request for investigations and prescriptions and comment on the effect on different quality measures associated with different telemedicine modalities used for primary care services and primary care referrals to secondary care Design and setting: Systematic review in primary care Methods: A systematic search was carried out across three databases (Medline, PubMed and Scopus) between August and November 2023, using terms related to telemedicine, general practice, electronic referrals, follow-up, use and efficiency and supported by citation searching. This was followed by screening according to pre-defined criteria, data extraction and critical appraisal. Narrative synthesis and metanalysis of quantitative data was used to summarize findings. Results: The search identified 2230 studies; 50 studies are included in this review. There was a prevalence of asynchronous modalities in both primary care services (68%) and referrals from primary care to secondary care (83%), and most of the study participants were females (63.3%), with mean age of 48.2. The average follow-up for virtual consultations in primary care was 28.4% (eVisits: 36.8%, secure messages 18.7%, videoconference 23.5%) with no significant difference between them or F2F consultations. There was an average annual reduction of primary care visits by 0.09/patient, an increase in telephone visits by 0.20/patient, an increase in ED encounters by 0.011/patient, an increase in hospitalizations by 0.02/patient and an increase in out of hours visits by 0.019/patient. Laboratory testing was requested on average for 10.9% of telemedicine patients, imaging or procedures for 5.6% and prescriptions for 58.7% of patients. When looking at referrals to secondary care, on average 36.7% of virtual referrals required follow-up visit, with the average rate of follow-up for electronic referrals being higher than for videoconferencing (39.2% vs 23%, p=0.167). Technical failures were reported on average for 1.4% of virtual consultations to primary care. When using carbon footprint estimates, we calculate that the use of telemedicine in primary care services can potentially provide a net decrease in carbon footprint by 0.592kgCO2/patient/year. When follow-up rates are taken into account, we estimate that virtual consultations reduce carbon footprint for primary care services by 2.3 times, and for secondary care referrals by 2.2 times. No major concerns regarding quality of care, or patient satisfaction were identified. 5/7 studies that addressed cost-effectiveness, reported increased savings. Conclusions: Telemedicine provides quality, cost-effective, and environmentally sustainable care for patients in primary care with inconclusive evidence regarding the rates of subsequent healthcare utilization. The evidence is limited by heterogeneous, small-scale studies and lack of prospective comparative studies. Further research to identify the most appropriate telemedicine modality for different patient populations, clinical presentations, service provision (e.g. used to follow-up patients instead of initial diagnosis) as well as further education for patients and providers alike on how to make best use of this service is expected to improve outcomes and influence practice.Keywords: telemedicine, healthcare utilisation, digital interventions, environmental impact, sustainable healthcare
Procedia PDF Downloads 573988 Optimization of Agricultural Water Demand Using a Hybrid Model of Dynamic Programming and Neural Networks: A Case Study of Algeria
Authors: M. Boudjerda, B. Touaibia, M. K. Mihoubi
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In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.Keywords: water management, agricultural demand, dam and reservoir operation, Foum el-Gherza dam, dynamic programming, artificial neural network
Procedia PDF Downloads 1153987 A Two Level Load Balancing Approach for Cloud Environment
Authors: Anurag Jain, Rajneesh Kumar
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Cloud computing is the outcome of rapid growth of internet. Due to elastic nature of cloud computing and unpredictable behavior of user, load balancing is the major issue in cloud computing paradigm. An efficient load balancing technique can improve the performance in terms of efficient resource utilization and higher customer satisfaction. Load balancing can be implemented through task scheduling, resource allocation and task migration. Various parameters to analyze the performance of load balancing approach are response time, cost, data processing time and throughput. This paper demonstrates a two level load balancer approach by combining join idle queue and join shortest queue approach. Authors have used cloud analyst simulator to test proposed two level load balancer approach. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.Keywords: cloud analyst, cloud computing, join idle queue, join shortest queue, load balancing, task scheduling
Procedia PDF Downloads 4313986 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 833985 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 263984 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 1703983 Embedded Hybrid Intuition: A Deep Learning and Fuzzy Logic Approach to Collective Creation and Computational Assisted Narratives
Authors: Roberto Cabezas H
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The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance
Procedia PDF Downloads 1423982 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 2983981 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 963980 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 4083979 Academic Staff Identity and Emotional Labour: Exploring Pride, Motivation, and Relationships in Universities
Authors: Keith Schofield, Garry R. Prentice
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The perceptions of the work an academic does, and the environment in which they do it, contributes to the professional identity of that academic. In turn, this has implications for the level of involvement they have in their job, their satisfaction, and their work product. This research explores academic identities in British and Irish institutions and considers the complex interplay between identity, practice, and participation. Theoretical assumptions made in this paper assert that meaningful work has positive effects on work pride, organisational commitment, organisational citizenship, and motivation; when employees participate enthusiastically they are likely to be more engaged, more successful, and more satisfied. Further examination is given to the context in which this participation happens; the nature of institutional process, management, and relationships with colleagues, team members, and students is considered. The present study follows a mixed-methods approach to explore work satisfaction constructs in a number of academic contexts in the UK and Ireland. The quantitative component of this research (Convenience Sample: 155 academics, and support/ administrative staff; 36.1% male, 63.9% female; 60.8% academic staff, 39.2% support/ administration staff; across a number of universities in the UK and Ireland) was based on an established emotional labour model and was tested across gender groups, job roles, and years of service. This was complimented by qualitative semi-structured interviews (Purposive Sample: 10 academics, and 5 support/ administrative staff across the same universities in the UK and Ireland) to examine various themes including values within academia, work conditions, professional development, and transmission of knowledge to students. Experiences from both academic and support perspectives were sought in order to gain a holistic view of academia and to provide an opportunity to explore the dynamic of the academic/administrator relationship within the broader institutional context. The quantitative emotional labour model, tested via a path analysis, provided a robust description of the relationships within the data. The significant relationships found within the quantitative emotional labour model included a link between non-expression of true feelings resulting in emotional labourious work and lower levels of intrinsic motivation and higher levels of extrinsic motivation. Higher levels of intrinsic motivation also linked positively to work pride. These findings were further explored in the qualitative elements of the research where themes emerged including the disconnection between faculty management and staff, personal fulfilment and the friction between the identities of teacher, researcher/ practitioner and administrator. The implications of the research findings from this study are combined and discussed in relation to possible identity-related and emotional labour management-related interventions. Further, suggestions are made to institutions concerning the application of these findings including the development of academic practices, with specific reference to the duality of identity required to service the combined teacher/ researcher role. Broader considerations of the paper include how individuals and institutions may engage with the changing nature of students-as-consumers as well as a recommendation to centralise personal fulfillment through the development of professional academic identities.Keywords: academic work, emotional labour, identity friction, mixed methods
Procedia PDF Downloads 2763978 Interpretable Deep Learning Models for Medical Condition Identification
Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji
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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.Keywords: deep learning, interpretability, attention, big data, medical conditions
Procedia PDF Downloads 913977 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 2963976 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 3263975 Teaching Reading in English: The Neglect of Phonics in Nigeria
Authors: Abdulkabir Abdullahi
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Nigeria has not yet welcomed phonics into its primary schools. In government-owned primary schools teachers are functionally ignorant of the stories of the reading wars amongst international scholars. There are few or no Nigerian-authored phonics textbooks, and there has been no government-owned phonics curriculum either. There are few or no academic journal articles on phonics in the country and there is, in fact, a certain danger of confusion between phonics and phonetics among Nigerian publishers, authors, writers and academics as if Nigerian teachers of English and the educational policy makers of the country were unaware of reading failures/problems amongst Nigerian children, or had never heard of phonics or read of the stories of the reading wars or the annual phonics test in the United Kingdom, the United States of America and other parts of the world. It is on this note that this article reviews and examines, in the style of a qualitative inquiry, the body of arguments on phonics, and explores the effectiveness of phonics teaching, particularly, in a second-language learning contexts. While the merit of the paper is, perhaps, situated in its supreme effort to draw global attention to reading failures/problems in Nigeria and the ways the situation may affect English language learning, international academic relations and the educational future of the country, it leaves any quantitative verification of its claims to interested quantitative researchers in the world.Keywords: graphemes, phonics, reading, reading wars, reading theories, phonemic awareness
Procedia PDF Downloads 2333974 Pibid and Experimentation: A High School Case Study
Authors: Chahad P. Alexandre
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PIBID-Institutional Program of Scholarships to Encourage Teaching - is a Brazilian government program that counts today with 48.000 students. It's goal is to motivate the students to stay in the teaching undergraduate programs and to help fill the gap of 100.000 teachers that are needed today in the under graduated schools. The major lack of teachers today is in physics, chemistry, mathematics, and biology. At IFSP-Itapetininga we formatted our physics PIBID based on practical activities. Our students are divided in two São Paulo state government high schools in the same city. The project proposes class activities based on experimentation, observation and understanding of physical phenomena. The didactical experiments are always in relation with the content that the teacher is working, he is the supervisor of the program in the school. Always before an experiment is proposed a little questionnaire to learn about the students preconceptions and one is filled latter to evaluate if now concepts have been created. This procedure is made in order to compare their previous knowledge and how it changed after the experiment is developed. The primary goal of our project is to make the Physics class more attractive to the students and to develop in high school students the interest in learning physics and to show the relation of Physics to the day by day and to the technological world. The objective of the experimental activities is to facilitate the understanding of the concepts that are worked on classes because under experimentation the PIBID scholarship student stimulate the curiosity of the high school student and with this he can develop the capacity to understand and identify the physical phenomena with concrete examples. Knowing how to identify this phenomena and where they are present at the high school student life makes the learning process more significant and pleasant. This proposal make achievable to the students to practice science, to appropriate of complex, in the traditional classes, concepts and overcoming the common preconception that physics is something distant and that is present only on books. This preconception is extremely harmful in the process of scientific knowledge construction. This kind of learning – through experimentation – make the students not only accumulate knowledge but also appropriate it, also to appropriate experimental procedures and even the space that is provided by the school. The PIBID scholarship students, as future teachers also have the opportunity to try experimentation classes, to intervene in the classes and to have contact with their future career. This opportunity allows the students to make important reflection about the practices realized and consequently about the learning methods. Due to this project, we found out that the high school students stay more time focused in the experiment compared to the traditional explanation teachers´ class. As a result in a class, as a participative activity, the students got more involved and participative. We also found out that the physics under graduated students drop out percentage is smaller in our Institute than before the PIBID program started.Keywords: innovation, projects, PIBID, physics, pre-service teacher experiences
Procedia PDF Downloads 3413973 Lessons Learned from Covid19 - Related ERT in Universities
Authors: Sean Gay, Cristina Tat
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This presentation will detail how a university in Western Japan has implemented its English for Academic Purposes (EAP) program during the onset of CoViD-19 in the spring semester of 2020. In the spring semester of 2020, after a 2 week delay, all courses within the School of Policy Studies EAP Program at Kwansei Gakuin University were offered in an online asynchronous format. The rationale for this decision was not to disadvantage students who might not have access to devices necessary for taking part in synchronous online lessons. The course coordinators were tasked with consolidating the materials originally designed for face-to-face14 week courses for a 12 week asynchronous online semester and with uploading the modified course materials to Luna, the university’s network, which is a modified version of Blackboard. Based on research to determine the social and academic impacts of this CoViD-19 ERT approach on the students who took part in this EAP program, this presentation explains how future curriculum design and implementation can be managed in a post-CoViD world. There are a wide variety of lessons that were salient. The role of the classroom as a social institution was very prominent; however, awareness of cognitive burdens and strategies to mitigate that burden may be more valuable for teachers. The lessons learned during this period of ERT can help teachers moving forward.Keywords: asynchronous online learning, emergency remote teaching (ERT), online curriculum design, synchronous online learning
Procedia PDF Downloads 2033972 Studying Educational Processes through a Multifocal Viewpoint: Educational and Social Studies
Authors: Noa Shriki, Atara Shriki
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Lifelong learning is considered as essential for teacher's professional development, which in turn has implications for the improvement of the entire education system. In recent years, many programs designed to support teachers' professional development are criticized for not achieving their goal. A variety of reasons have been proposed for the purpose of explaining the causes of the ineffectiveness of such programs. In this study, we put to test the possibility that teachers do not change as a result of their participation in professional programs due to a gap between the contents and approaches included in them and teacher's beliefs about teaching and learning. Eighteen elementary school mathematics teachers participated in the study. These teachers were involved in collaborating with their students in inquiring mathematical ideas, while implementing action research. Employing educational theories, the results indicated that this experience had a positive effect on teacher's professional development. In particular, there was an evident change in their beliefs regarding their role as mathematics teachers. However, while employing a different perspective for analyzing the data, the lens of Kurt Lewin's theory of re-education, we realized that this change of beliefs must be questioned. Therefore, it is suggested that analysis of educational processes should be carried out not only through common educational theories, but also on the basis of social and organizational theories. It is assumed that both the field of education and the fields of social studies and organizational consulting will benefit from the multifocal viewpointKeywords: educational theories, professional development, re-education, teachers' beliefs
Procedia PDF Downloads 141