Search results for: architectural design learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18747

Search results for: architectural design learning

16767 Traditional Wisdom of Indigenous Vernacular Architecture as Tool for Climate Resilience Among PVTG Indigenous Communities in Jharkhand, India

Authors: Ankush, Harshit Sosan Lakra, Rachita Kuthial

Abstract:

Climate change poses significant challenges to vulnerable communities, particularly indigenous populations in ecologically sensitive regions. Jharkhand, located in the heart of India, is home to several indigenous communities, including the Particularly Vulnerable Tribal Groups (PVTGs). The Indigenous architecture of the region functions as a significant reservoir of climate adaptation wisdom. It explores the architectural analysis encompassing the construction materials, construction techniques, design principles, climate responsiveness, cultural relevance, adaptation, integration with the environment and traditional wisdom that has evolved through generations, rooted in cultural and socioeconomic traditions, and has allowed these communities to thrive in a variety of climatic zones, including hot and dry, humid, and hilly terrains to withstand the test of time. Despite their historical resilience to adverse climatic conditions, PVTG tribal communities face new and amplified challenges due to the accelerating pace of climate change. There is a significant research void that exists in assimilating their traditional practices and local wisdom into contemporary climate resilience initiatives. Most of the studies place emphasis on technologically advanced solutions, often ignoring the invaluable Indigenous Local knowledge that can complement and enhance these efforts. This research gap highlights the need to bridge the disconnect between indigenous knowledge and contemporary climate adaptation strategies. The study aims to explore and leverage indigenous knowledge of vernacular architecture as a strategic tool for enhancing climatic resilience among PVTGs of the region. The first objective is to understand the traditional wisdom of vernacular architecture by analyzing and documenting distinct architectural practices and cultural significance of PVTG communities, emphasizing construction techniques, materials and spatial planning. The second objective is to develop culturally sensitive climatic resilience strategies based on findings of vernacular architecture by employing a multidisciplinary research approach that encompasses ethnographic fieldwork climate data assessment considering multiple variables such as temperature variations, precipitation patterns, extreme weather events and climate change reports. This will be a tailor-made solution integrating indigenous knowledge with modern technology and sustainable practices. With the involvement of indigenous communities in the process, the research aims to ensure that the developed strategies are practical, culturally appropriate, and accepted. To foster long-term resilience against the global issue of climate change, we can bridge the gap between present needs and future aspirations with Traditional wisdom, offering sustainable solutions that will empower PVTG communities. Moreover, the study emphasizes the significance of preserving and reviving traditional Architectural wisdom for enhancing climatic resilience. It also highlights the need for cooperative endeavors of communities, stakeholders, policymakers, and researchers to encourage integrating traditional Knowledge into Modern sustainable design methods. Through these efforts, this research will contribute not only to the well-being of PVTG communities but also to the broader global effort to build a more resilient and sustainable future. Also, the Indigenous communities like PVTG in the state of Jharkhand can achieve climatic resilience while respecting and safeguarding the cultural heritage and peculiar characteristics of its native population.

Keywords: vernacular architecture, climate change, resilience, PVTGs, Jharkhand, indigenous people, India

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16766 Proposing an Algorithm to Cluster Ad Hoc Networks, Modulating Two Levels of Learning Automaton and Nodes Additive Weighting

Authors: Mohammad Rostami, Mohammad Reza Forghani, Elahe Neshat, Fatemeh Yaghoobi

Abstract:

An Ad Hoc network consists of wireless mobile equipment which connects to each other without any infrastructure, using connection equipment. The best way to form a hierarchical structure is clustering. Various methods of clustering can form more stable clusters according to nodes' mobility. In this research we propose an algorithm, which allocates some weight to nodes based on factors, i.e. link stability and power reduction rate. According to the allocated weight in the previous phase, the cellular learning automaton picks out in the second phase nodes which are candidates for being cluster head. In the third phase, learning automaton selects cluster head nodes, member nodes and forms the cluster. Thus, this automaton does the learning from the setting and can form optimized clusters in terms of power consumption and link stability. To simulate the proposed algorithm we have used omnet++4.2.2. Simulation results indicate that newly formed clusters have a longer lifetime than previous algorithms and decrease strongly network overload by reducing update rate.

Keywords: mobile Ad Hoc networks, clustering, learning automaton, cellular automaton, battery power

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16765 Connecting Teachers in a Web-Based Professional Development Community in Crisis Time: A Knowledge Building Approach

Authors: Wei Zhao

Abstract:

The pandemic crisis disrupted normal classroom practices so that the constraints of the traditional practice became apparent. This turns out to be new opportunities for technology-based learning and teaching. However, how the technology supports the preschool teachers go through this sudden crisis and how preschool teachers conceived of the use of technology, appropriate and design technological artifacts as a mediator of knowledge construction in order to suit young children’s literacy level are rarely explored. This study addresses these issues by looking at the influence of a web-supported teacher community on changes/shifts in preschool teachers’ epistemological beliefs and practices. This teachers’ professional development community was formulated before the pandemic time and developed virtually throughout the home-based learning caused by Covid-19. It served as a virtual and asynchronous community for those teachers to collaboratively plan for and conduct online lessons using the knowledge-building approach for the purpose of sustaining children’s learning curiosity and opening up new learning opportunities during the lock-down period. The knowledge-building approach helps to increase teachers’ collective responsibility to collaboratively work on shared educational goals in the teacher community and awareness of noticing new ideas or innovations in their classroom. Based on the data collected across five months during and after the lock-down period and the activity theory, results show a dynamic interplay between the evolution of the community culture, the growth of teacher community and teachers’ identity transformation and professional development. Technology is useful in this regard not only because it transforms the geographical distance and new gathering guidelines after the outbreak of pandemic into new ways of communal communication and collaboration. More importantly, while teachers selected, monitored and adapted the technology, it acts as a catalyst for changes in teachers’ old teaching practices and epistemological dispositions.

Keywords: activity theory, changes in epistemology and practice, knowledge building, web-based teachers’ professional development community

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16764 Count of Trees in East Africa with Deep Learning

Authors: Nubwimana Rachel, Mugabowindekwe Maurice

Abstract:

Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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16763 Carbon Skimming: Towards an Application to Summarise and Compare Embodied Carbon to Aid Early-Stage Decision Making

Authors: Rivindu Nethmin Bandara Menik Hitihamy Mudiyanselage, Matthias Hank Haeusler, Ben Doherty

Abstract:

Investors and clients in the Architectural, Engineering and Construction industry find it difficult to understand complex datasets and reports with little to no graphic representation. The stakeholders examined in this paper include designers, design clients and end-users. Communicating embodied carbon information graphically and concisely can aid with decision support early in a building's life cycle. It is essential to create a common visualisation approach as the level of knowledge about embodied carbon varies between stakeholders. The tool, designed in conjunction with Bates Smart, condenses Tally Life Cycle Assessment data to a carbon hot-spotting visualisation, highlighting the sections with the highest amounts of embodied carbon. This allows stakeholders at every stage of a given project to have a better understanding of the carbon implications with minimal effort. It further allows stakeholders to differentiate building elements by their carbon values, which enables the evaluation of the cost-effectiveness of the selected materials at an early stage. To examine and build a decision-support tool, an action-design research methodology of cycles of iterations was used along with precedents of embodied carbon visualising tools. Accordingly, the importance of visualisation and Building Information Modelling are also explored to understand the best format for relaying these results.

Keywords: embodied carbon, visualisation, summarisation, data filtering, early-stage decision-making, materiality

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16762 Active Learning Role on Strategic I-Map Thinking in Developing Reasoning Thinking and the Intrinsic-Motivation Orientation

Authors: Khaled Alotaibi

Abstract:

This paper deals with developing reasoning thinking and the intrinsic-extrinsic motivation for learning, and enhancing the academic achievement of a sample of students at Teachers' College in King Saud University. The study sample included 58 students who were divided randomly into two groups; one was an experimental group with 20 students and the other was a control group with 22 students. The following tools were used: e-courses by using I-map, Reasoning Thinking Tes, questionnaire to measure the intrinsic-extrinsic motivation for learning and an academic achievement test. Experimental group was taught using e-courses by using I-map, while the control group was taught by using traditional education. The results showed that: - There were no statistically significant differences between the experimental group and the control group in Reasoning thinking skills. - There were statistically significant differences between the experimental group and the control group in the intrinsic-extrinsic motivation for learning in favor of the experimental group. - There were statistically significant differences between the experimental group and the control group in academic achievement in favor of the experimental group.

Keywords: reasoning, thinking, intrinsic motivation, active learning

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16761 Descriptive Study of Role Played by Exercise and Diet on Brain Plasticity

Authors: Mridul Sharma, Praveen Saroha

Abstract:

In today's world, everyone has become so busy in their to-do tasks and daily routine that they tend to ignore some of the basal components of our life, including exercise and diet. This comparative study analyzes the pathways of the relationship between exercise and brain plasticity and also includes another variable diet to study the effects of diet on learning by answering questions including which diet is known to be the best learning supporter and what are the recommended quantities of the same. Further, this study looks into inter-relation between diet and exercise, and also some other approach of the relation between diet and exercise on learning apart from through Brain Derived Neurotrophic Factor (BDNF).

Keywords: brain derived neurotrophic factor, brain plasticity, diet, exercise

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16760 Architectural Wind Data Maps Using an Array of Wireless Connected Anemometers

Authors: D. Serero, L. Couton, J. D. Parisse, R. Leroy

Abstract:

In urban planning, an increasing number of cities require wind analysis to verify comfort of public spaces and around buildings. These studies are made using computer fluid dynamic simulation (CFD). However, this technique is often based on wind information taken from meteorological stations located at several kilometers of the spot of analysis. The approximated input data on project surroundings produces unprecise results for this type of analysis. They can only be used to get general behavior of wind in a zone but not to evaluate precise wind speed. This paper presents another approach to this problem, based on collecting wind data and generating an urban wind cartography using connected ultrasound anemometers. They are wireless devices that send immediate data on wind to a remote server. Assembled in array, these devices generate geo-localized data on wind such as speed, temperature, pressure and allow us to compare wind behavior on a specific site or building. These Netatmo-type anemometers communicate by wifi with central equipment, which shares data acquired by a wide variety of devices such as wind speed, indoor and outdoor temperature, rainfall, and sunshine. Beside its precision, this method extracts geo-localized data on any type of site that can be feedback looped in the architectural design of a building or a public place. Furthermore, this method allows a precise calibration of a virtual wind tunnel using numerical aeraulic simulations (like STAR CCM + software) and then to develop the complete volumetric model of wind behavior over a roof area or an entire city block. The paper showcases connected ultrasonic anemometers, which were implanted for an 18 months survey on four study sites in the Grand Paris region. This case study focuses on Paris as an urban environment with multiple historical layers whose diversity of typology and buildings allows considering different ways of capturing wind energy. The objective of this approach is to categorize the different types of wind in urban areas. This, particularly the identification of the minimum and maximum wind spectrum, helps define the choice and performance of wind energy capturing devices that could be implanted there. The localization on the roof of a building, the type of wind, the altimetry of the device in relation to the levels of the roofs, the potential nuisances generated. The method allows identifying the characteristics of wind turbines in order to maximize their performance in an urban site with turbulent wind.

Keywords: computer fluid dynamic simulation in urban environment, wind energy harvesting devices, net-zero energy building, urban wind behavior simulation, advanced building skin design methodology

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16759 Women Learning in Creative Project Based Learning of Engineering Education

Authors: Jui Hsuan Hung, Jeng Yi Tzeng

Abstract:

Engineering education in the higher education is always male dominated. Therefore, women learning in this environment is an important research topic for feminists, gender researchers and engineering education researchers, especially in the era of gender mainstreaming. The research topics are from the dialectical discussion of feminism and science development history, gender issues of science education, to the subject choice of female students. These researches enrich the field of gender study in engineering education but lack of describing the detailed images of women in engineering education, including their learning, obstacles, needs or feelings. Otherwise, in order to keep up with the industrial trends of emphasizing group collaboration, engineering education turns from traditional lecture to creative group inquiry pedagogy in recent years. Creative project based learning is one of the creative group inquiry pedagogy which the engineering education in higher education adopts often, and it is seen as a gender-inclusive pedagogy in engineering education. Therefore, in order to understand the real situation of women learning in engineering education, this study took place in a course (Introduction to Engineering) offered by the school of engineering of a university in Taiwan. This course is designed for freshman students to establish basic understanding engineering from four departments (Chemical Engineering, Power Mechanical Engineering, Materials Science, Industrial Engineering and Engineering Management). One section of this course is to build a Hydraulic Robot designed by the Department of Power Mechanical Engineering. 321 students in the school of engineering took this course and all had the reflection questionnaire. These students are divided into groups of 5 members to work on this project. The videos of process of discussion of five volunteered groups with different gender composition are analyzed, and six women of these five groups are interviewed. We are still on the process of coding and analyzing videos and the qualitative data, but several tentative findings have already emerged. (1) The activity models of groups of both genders are gender segregation, and not like women; men never be the ‘assistants’. (2) The culture of the group is developed by the major gender, but men always dominate the process of practice in all kinds of gender composition groups. (3) Project based learning is supposed to be a gender-inclusive learning model in creative engineering education, but communication obstacles between men and women make it less women friendly. (4) Gender identity, not professional identity, is adopted by these women while they interact with men in their groups. (5) Gender composition and project-based learning pedagogy are not the key factors for women learning in engineering education, but the gender conscience awareness is.

Keywords: engineering education, gender education, creative project based learning, women learning

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16758 Downscaling Seasonal Sea Surface Temperature Forecasts over the Mediterranean Sea Using Deep Learning

Authors: Redouane Larbi Boufeniza, Jing-Jia Luo

Abstract:

This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.

Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning

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16757 Learning Communities and Collaborative Reflection for Teaching Improvement

Authors: Mariana Paz Sajon, Paula Cecilia Primogerio, Mariana Albarracin

Abstract:

This study recovers an experience of teacher training carried out in an Undergraduate Business School from a private university in Buenos Aires, Argentina. The purpose of the project was to provide teachers with an opportunity to reflect on their teaching practices at the university. The aim of the study is to systematize lessons and challenges that emerge from this teacher training experience. A group of teachers who showed a willingness to learn teaching abilities was selected to work. They completed a formative journey working in learning communities starting from the immersion in different aspects of teaching and learning, class observations, and an individual and collaborative reflection exercise in a systematic way among colleagues. In this study, the productions of the eight teachers who are members of the learning communities are analyzed, framed in an e-portfolio that they prepared during the training journey. The analysis shows that after the process of shared reflection, traits related to powerful teaching and meaningful learning have appeared in the classes. For their part, teachers reflect having reached an awareness of their own practices, identifying strengths and opportunities for improvement, and the experience of sharing their own way and knowing the successes and failures of others was valued. It is an educational journey of pedagogical transformation of the teachers, which is infrequent in business education, which could lead to a change in teaching practices for the entire Business School. The present study involves theoretical and pedagogic aspects of education in a business school in Argentina and its flow-on implications for the workplace that may be transferred to other educational contexts.

Keywords: Argentina, learning community, meaningful learning, powerful teaching, reflective practice

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16756 English Learning Motivation in Communicative Competence

Authors: Sebastianus Menggo

Abstract:

The aim of communicative language teaching is to enable learners to communicate in the target language. Each learner is required to perform the micro and macro components in each utterance produced. Utterances produced must be in line with the understanding of competence and performance of each speaker. These are inter-depended. Competence and performance are obliged to be appeared proportionally in creating the utterances. The representative of competence and performance reflects the linguistics identity of a speaker in providing sentences in each certain language community. Each lexicon spoken may lead that interlocutor in comprehending the intentions utterances given. However proportional performance of both components in an utterance needed to be further elaborated. Finding appropriate gap between competence and performance components in a communicative competence must be supported positive response given by the learners.The learners’ inability to keep communicative competence proportionally is caused by inside and outside factors. The inside factors are certain lacks such as lack of self-confidence and lack of motivation which could make students feel ashamed to produce utterances, scared to make mistakes, and have no enough confidence. Knowing learner’s English learning motivation is an urgent variable to be considered in creating conducive atmosphere classroom which will raise the learners to do more toward the achievement of communicative competence. Meanwhile, the outside factor is related with the teacher. The teacher should be able to recognize the students’ problem in creating conducive atmosphere in the classroom that will raise the students’ ability to be an English speaker qualified. Moreover, the aim of this research is to know and describe the English learning motivation affecting students’ communicative competence of 48 students of XI grade of science program at catholic senior of Saint Ignasius Loyola Labuan Bajo, West Flores, Indonesia. Correlation design with purposive procedure applied in this research. Data were collected through questionnaire, interview, and students’ speaking achievement document. Result shows the description of motivation significantly affecting students’ communicative competence.

Keywords: communicative, competence, English, learning, motivation

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16755 Adaptive Assemblies: A Scalable Solution for Atlanta's Affordable Housing Crisis

Authors: Claudia Aguilar, Amen Farooq

Abstract:

Among other cities in the United States, the city of Atlanta is experiencing levels of growth that surpass anything we have witnessed in the last century. With the surge of population influx, the available housing is practically bursting at the seams. Supply is low, and demand is high. In effect, the average one-bedroom apartment runs for 1,800 dollars per month. The city is desperately seeking new opportunities to provide affordable housing at an expeditious rate. This has been made evident by the recent updates to the city’s zoning. With the recent influx in the housing market, young professionals, in particular millennials, are desperately looking for alternatives to stay within the city. To remedy Atlanta’s affordable housing crisis, the city of Atlanta is planning to introduce 40 thousand of new affordable housing units by 2026. To achieve the urgent need for more affordable housing, the architectural response needs to adapt to overcome this goal. A method that has proven successful in modern housing is to practice modular means of development. A method that has been constrained to the dimensions of the max load for an eighteen-wheeler. This approach has diluted the architect’s ability to produce site-specific, informed design and rather contributes to the “cookie cutter” stigma that the method has been labeled with. This thesis explores the design methodology for modular housing by revisiting its constructability and adaptability. This research focuses on a modular housing type that could break away from the constraints of transport and deliver adaptive reconfigurable assemblies. The adaptive assemblies represent an integrated design strategy for assembling the future of affordable dwelling units. The goal is to take advantage of a component-based system and explore a scalable solution to modular housing. This proposal aims specifically to design a kit of parts that are made to be easily transported and assembled but also gives the ability to customize the use of components to benefit all unique conditions. The benefits of this concept could include decreased construction time, cost, on-site labor, and disruption while providing quality housing with affordable and flexible options.

Keywords: adaptive assemblies, modular architecture, adaptability, constructibility, kit of parts

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16754 FPGA Implementation of RSA Encryption Algorithm for E-Passport Application

Authors: Khaled Shehata, Hanady Hussien, Sara Yehia

Abstract:

Securing the data stored on E-passport is a very important issue. RSA encryption algorithm is suitable for such application with low data size. In this paper the design and implementation of 1024 bit-key RSA encryption and decryption module on an FPGA is presented. The module is verified through comparing the result with that obtained from MATLAB tools. The design runs at a frequency of 36.3 MHz on Virtex-5 Xilinx FPGA. The key size is designed to be 1024-bit to achieve high security for the passport information. The whole design is achieved through VHDL design entry which makes it a portable design and can be directed to any hardware platform.

Keywords: RSA, VHDL, FPGA, modular multiplication, modular exponential

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16753 Deep Learning Approaches for Accurate Detection of Epileptic Seizures from Electroencephalogram Data

Authors: Ramzi Rihane, Yassine Benayed

Abstract:

Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures resulting from abnormal electrical activity in the brain. Timely and accurate detection of these seizures is essential for improving patient care. In this study, we leverage the UK Bonn University open-source EEG dataset and employ advanced deep-learning techniques to automate the detection of epileptic seizures. By extracting key features from both time and frequency domains, as well as Spectrogram features, we enhance the performance of various deep learning models. Our investigation includes architectures such as Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), 1D Convolutional Neural Networks (1D-CNN), and hybrid CNN-LSTM and CNN-BiLSTM models. The models achieved impressive accuracies: LSTM (98.52%), Bi-LSTM (98.61%), CNN-LSTM (98.91%), CNN-BiLSTM (98.83%), and CNN (98.73%). Additionally, we utilized a data augmentation technique called SMOTE, which yielded the following results: CNN (97.36%), LSTM (97.01%), Bi-LSTM (97.23%), CNN-LSTM (97.45%), and CNN-BiLSTM (97.34%). These findings demonstrate the effectiveness of deep learning in capturing complex patterns in EEG signals, providing a reliable and scalable solution for real-time seizure detection in clinical environments.

Keywords: electroencephalogram, epileptic seizure, deep learning, LSTM, CNN, BI-LSTM, seizure detection

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16752 Vocational Education: A Synergy for Skills Acquisition and Global Learning in Colleges of Education in Ogun State, Nigeria

Authors: Raimi, Kehinde Olawuyi, Omoare Ayodeji Motunrayo

Abstract:

In the last two decades, there has been rising youth unemployment, restiveness, and social vices in Nigeria. The relevance of Vocational Education for skills acquisition, global learning, and national development to address these problems cannot be underestimated. Thus, the need to economically empower Nigerian youths to be able to develop the nation and meet up in the ever-changing global learning and economy led to the assessment of Vocational Education as Synergy for the Skills Acquisition and Global Learning in Ogun State, Nigeria. One hundred and twenty out of 1,500 students were randomly selected for this study. Data were obtained through a questionnaire and were analyzed with descriptive statistics and Chi-square. The results of the study showed that 59.2% of the respondents were between 20 – 24 years of age, 60.8% were male, and 65.8% had a keen interest in Vocational Education. Also, 90% of the respondents acquired skills in extension/advisory, 78.3% acquired skills in poultry production, and 69.1% acquired skills in fisheries/aquaculture. The major constraints to Vocational Education are inadequate resource personnel (χ² = 10.25, p = 0.02), inadequate training facilities (x̅ = 2.46) and unstable power supply (x̅ = 2.38). Results of Chi-square showed significance association between constraints and Skills Acquisition (χ² = 12.54, p = 0.00) at p < 0.05 level of significance. It was established that Vocational Education significantly contributed to students’ skills acquisition and global learning. This study, therefore, recommends that inadequate personnel should be looked into by the school authority in order not to over-stretch the available staff of the institution while the provision of alternative stable power supply (solar power) is also essential for effective teaching and learning process.

Keywords: vocational education, skills acquisition, national development, global learning

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16751 The Role of Communicative Grammar in Cross-Cultural Learning Environment

Authors: Tonoyan Lusine

Abstract:

The Communicative Grammar (CG) of a language deals with semantics and pragmatics in the first place as communication is a process of generating speech. As it is well known people can communicate with the help of limited word expressions and grammatical means. As to non-verbal communication, both vocabulary and grammar are not essential at all. However, the development of the communicative competence lies in verbal, non-verbal, grammatical, socio-cultural and intercultural awareness. There are several important issues and environment management strategies related to effective communication that one might need to consider for a positive learning experience. International students bring a broad range of cultural perspectives to the learning environment, and this diversity has the capacity to improve interaction and to enrich the teaching/learning process. Intercultural setting implies creative and thought-provoking work with different cultural worldviews and international perspectives. It is worth mentioning that the use of Communicative Grammar models creates a profound background for the effective intercultural communication.

Keywords: CG, cross-cultural communication, intercultural awareness, non-verbal behavior

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16750 Teaching Practitioners to Use Technology to Support and Instruct Students with Autism Spectrum Disorders

Authors: Nicole Nicholson, Anne Spillane

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The purpose of this quantitative, descriptive analysis was to determine the success of a post-graduate new teacher education program, designed to teach educators the knowledge and skills necessary to use technology in the classroom, improve the ability to communicate with stakeholders, and implement EBPs and UDL principles into instruction for students with ASD (Autism Spectrum Disorders ). The success of candidates (n=20) in the program provided evidence as to how candidates were effectively able to use technology to create meaningful learning opportunities and implement EBPs for individuals with ASD. ≥90% of participants achieved the following competencies: podcast creation; technology used to share information about assistive technology; and created a resource website on ASD (including information on EBPs, local and national support groups, ASD characteristics, and the latest research on ASD). 59% of students successfully created animation. Results of the analysis indicated that the teacher education program was successful in teaching candidates desired competencies during its first year of implementation.

Keywords: autism spectrum disorders, ASD, evidence based practices, EBP, universal design for learning, UDL

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16749 Training for Digital Manufacturing: A Multilevel Teaching Model

Authors: Luís Rocha, Adam Gąska, Enrico Savio, Michael Marxer, Christoph Battaglia

Abstract:

The changes observed in the last years in the field of manufacturing and production engineering, popularly known as "Fourth Industry Revolution", utilizes the achievements in the different areas of computer sciences, introducing new solutions at almost every stage of the production process, just to mention such concepts as mass customization, cloud computing, knowledge-based engineering, virtual reality, rapid prototyping, or virtual models of measuring systems. To effectively speed up the production process and make it more flexible, it is necessary to tighten the bonds connecting individual stages of the production process and to raise the awareness and knowledge of employees of individual sectors about the nature and specificity of work in other stages. It is important to discover and develop a suitable education method adapted to the specificities of each stage of the production process, becoming an extremely crucial issue to exploit the potential of the fourth industrial revolution properly. Because of it, the project “Train4Dim” (T4D) intends to develop complex training material for digital manufacturing, including content for design, manufacturing, and quality control, with a focus on coordinate metrology and portable measuring systems. In this paper, the authors present an approach to using an active learning methodology for digital manufacturing. T4D main objective is to develop a multi-degree (apprenticeship up to master’s degree studies) and educational approach that can be adapted to different teaching levels. It’s also described the process of creating the underneath methodology. The paper will share the steps to achieve the aims of the project (training model for digital manufacturing): 1) surveying the stakeholders, 2) Defining the learning aims, 3) producing all contents and curriculum, 4) training for tutors, and 5) Pilot courses test and improvements.

Keywords: learning, Industry 4.0, active learning, digital manufacturing

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16748 MLProxy: SLA-Aware Reverse Proxy for Machine Learning Inference Serving on Serverless Computing Platforms

Authors: Nima Mahmoudi, Hamzeh Khazaei

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Serving machine learning inference workloads on the cloud is still a challenging task at the production level. The optimal configuration of the inference workload to meet SLA requirements while optimizing the infrastructure costs is highly complicated due to the complex interaction between batch configuration, resource configurations, and variable arrival process. Serverless computing has emerged in recent years to automate most infrastructure management tasks. Workload batching has revealed the potential to improve the response time and cost-effectiveness of machine learning serving workloads. However, it has not yet been supported out of the box by serverless computing platforms. Our experiments have shown that for various machine learning workloads, batching can hugely improve the system’s efficiency by reducing the processing overhead per request. In this work, we present MLProxy, an adaptive reverse proxy to support efficient machine learning serving workloads on serverless computing systems. MLProxy supports adaptive batching to ensure SLA compliance while optimizing serverless costs. We performed rigorous experiments on Knative to demonstrate the effectiveness of MLProxy. We showed that MLProxy could reduce the cost of serverless deployment by up to 92% while reducing SLA violations by up to 99% that can be generalized across state-of-the-art model serving frameworks.

Keywords: serverless computing, machine learning, inference serving, Knative, google cloud run, optimization

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16747 Using Integrative Assessment in Distance Learning: The Case of Department of Education - Navotas City

Authors: Meduranda Marco

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This paper aimed to discuss the Integrative Assessment (IA) initiative of the Schools Division Office - Navotas City. The introduction provided a brief landscape analysis of the current state of education, the context of SDO Navotas, and the rationale for the administration of Integrative Assessment (IA) in schools. The IA methodology, procedure, and implementation activities were also shared. Feedback and reports on IA showed positive results as all schools in the Division were able to operationalize IA and consequently foster academic ease for learners and parents. Challenges met after compliance were also documented and strategies to continuously improve the Integrative Assessment process were proposed.

Keywords: distance learning assessment, integrative assessment, academic ease, learning outcomes evaluation

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16746 Relationship between Effective Classroom Management with Students’ Academic Achievement of EFL of STKIP YPUP

Authors: Eny Syatriana

Abstract:

The purpose of this study is to find out the effective instruction for classroom management, with the main identification of organizing and managing effective learning environments, to identify characteristics of effective lesson planning, identify resources and materials dealing with positive and effective classroom management. Knowing the effective instruction management is one of the characteristics of well managed teacher. The study was carried out in three randomly selected classes of STKIP YPUP in South Sulawesi. The design adopted for the study was a descriptive survey approach. Simple descriptive analysis was used. The major instrument used in this study were student questionnaire, teacher questionnaire, data were gathered with the research instrument and were analyzed, the research question were investigated and two hypothesis were duly tested using t-test statistics. Based on the findings of this research, it was concluded that effective classroom management skills or techniques have strong and positive influence on student achievement.

Keywords: effective classroom management skills, students’ achievement, students academic, effective learning environments

Procedia PDF Downloads 334
16745 A Program Evaluation of TALMA Full-Year Fellowship Teacher Preparation

Authors: Emilee M. Cruz

Abstract:

Teachers take part in short-term teaching fellowships abroad, and their preparation before, during, and after the experience is critical to affecting teachers’ feelings of success in the international classroom. A program evaluation of the teacher preparation within TALMA: The Israel Program for Excellence in English (TALMA) full-year teaching fellowship was conducted. A questionnaire was developed that examined professional development, deliberate reflection, and cultural and language immersion offered before, during, and after the short-term experience. The evaluation also surveyed teachers’ feelings of preparedness for the Israeli classroom and any recommendations they had for future teacher preparation within the fellowship program. The review suggests the TALMA program includes integrated professional learning communities between fellows and Israeli co-teachers, more opportunities for immersive Hebrew language learning, a broader professional network with Israelis, and opportunities for guided discussion with the TALMA community continued participation in TALMA events and learning following the full-year fellowship. Similar short-term international programs should consider the findings in the design of their participation preparation programs. The review also offers direction for future program evaluation of short-term participant preparation, including the need for frequent response item updates to match current offerings and evaluation of participant feelings of preparedness before, during, and after the full-year fellowship.

Keywords: educational program evaluation, international teaching, short-term teaching, teacher beliefs, teaching fellowship, teacher preparation

Procedia PDF Downloads 183
16744 Architectural Strategies for Designing Durable Steel Structural Systems

Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

Abstract:

Nowadays, steel structures are used for not only common buildings but also high-rise construction and wide span covering. The advanced methods of construction as well as the advanced structural connections have a great effect on architecture. However a better use of steel structural systems will be achieved with the deep understanding of steel structures specifications and their substantial advantages. On the other hand, the steel structures face to the different environmental factors such as air flow which cause erosion and corrosion. With the time passing, the amount of these steel mass damages and also the imposed stress will be increased. In other words, the position of erosion in steel structures related to existing stresses indicates that effective environmental conditions will gradually decrease the structural resistance of steel components and result in decreasing the durability of steel components. In this paper, the durability of different steel structural components is evaluated and on the basis of these stress, architectural strategies for designing the system and the components of steel structures is recognized in order to achieve an optimum life cycle.

Keywords: durability, bending stress, erosion in steel structure, life cycle

Procedia PDF Downloads 565
16743 Modern Forms and Aesthetics in Design

Authors: Chukwuma Anya, Mekwa Eme

Abstract:

The term ‘’FORM’’ in design could be referred to as the combination of various shapes of different sizes and assembling them in appropriate positions to achieve a unique figure of high aesthetic value. A deduction from this definition is that forms contribute immensely to the actualization of aesthetics in a building. When these various shapes and figures are properly assembled, it may give rise to a concept in design. However some architects and other designers either misuse or abuse the use of these shapes, hence resulting to a design imbalance, lack of uniformity and expression. This academic work is designed to educate the public on the proper usage of some regular shapes like circles, rectangles, pentagons, hexagons, triangles etc, to achieve a unique form in design. By the end of this work, one should be able to assemble different shapes to express different emotions of the mind, such as peace, love, confusion, war, and unity. Some elements of design, such as balance, stability, functionality and aesthetics, will also be achieved even as the building maintains its unique form.

Keywords: aesthetics, form, balance, stability

Procedia PDF Downloads 89
16742 Multi-Spectral Deep Learning Models for Forest Fire Detection

Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

Abstract:

Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

Procedia PDF Downloads 243
16741 Students' Perceptions of Social Media as a Means to Improve Their Language Skills

Authors: Bahia Braktia, Ana Marcela Montenegro Sanchez

Abstract:

Social media, such as Facebook, Twitter, and YouTube, has been used for teaching and learning for quite some time. These platforms have been proven to be a good tool to improve various language skills, students’ performance of the English language, motivation as well as trigger the authentic language interaction. However, little is known about the potential effects of social media usage on the learning performance of Arabic language learners. The present study explores the potential role that the social media technologies play in learning Arabic as a foreign language at a university in Southeast of United States. In order to investigate this issue, an online survey was administered to examine the perceptions and attitudes of American students learning Arabic. The research questions were: How does social media, specifically Facebook and Twitter, impact the students' Arabic language skills, and what is their attitude toward it? The preliminary findings of the study showed that students had a positive attitude toward the use of social media to enhance their Arabic language skills, and that they used a range of social media features to expose themselves to the Arabic language and communicate in Arabic with native Arabic speaking friends. More detailed findings will be shared in the light data analysis with the audience during the presentation.

Keywords: foreign language learning, social media, students’ perceptions, survey

Procedia PDF Downloads 216
16740 Learning in Multicultural Workspaces: A Case of Aged Care

Authors: Robert John Godby

Abstract:

To be responsive now and in the future, workplaces must address the demands of multicultural teams as they become more common elements of the global labor force. This is especially the case for aged care due to the aging population, industry growth and migrant recruitment. This research identifies influences on and improvements for learning in these environments. Its unique contribution is to illuminate how culturally diverse workplaces can work and learn together more effectively. A mixed-methods approach was used to gather data about this topic in two phases. Firstly, the research methods included a survey of 102 aged care workers around Australia from two multi-site aged care organisations. The questionnaire elicited both quantitative and qualitative data about worker characteristics and perspectives on working and learning in aged care. Secondly, a case study of one aged care worksite was formulated drawing on worksite information and interviews with workers. A review of the literature suggests that learning in multicultural work environments is influenced by three main factors: 1) the individual workers themselves, 2) their interaction with each other and 3) the environment in which they work. There are various accounts of these three factors, how they are manifested and how they lead to a change in workers’ disposition, knowledge, or expertise when confronted with new circumstances. The study has found that a key individual factor influencing learning is cultural background. Their unique view of the world was shown to affect their approach to both their work and co-working. Interactional factors suggest that the high requirement for collaboration in aged care positively supports learning in this context; however, it can be hindered by cultural bias and spoken accent. The study also found that environmental factors, such as disruptions caused by the pandemic, were another key influence. For example, the need to wear face masks hindered the communication needed for workplace learning. This was especially challenging due to the diverse language backgrounds and abilities within the teams. Potential improvements for learning in multicultural aged care work environments were identified. These include more frequent and structured inter-peer learning (e.g. buddying), communication training (e.g. English language usage for both native and non-native speaking workers) and support for cross-cultural habitude (e.g. recognizing and adapting to cultural differences). Workplace learning in cross-cultural aged care environments is an area that is not extensively dealt with in the literature. This study addresses this gap and holds the potential to contribute practical insights to aged care and other diverse industries.

Keywords: cross-cultural learning, learning in aged care, migrant learning, workplace learning

Procedia PDF Downloads 163
16739 Impact of Organic Architecture in Building Design

Authors: Zainab Yahaya Suleiman

Abstract:

Physical fitness, as one of the most important keys to a healthy wellbeing, is the basis of dynamic and creative intellectual activity. As a result, the fitness world is expanding every day. It is believed that a fitness centre is a place of healing and also the natural environment is vital to speedy recovery. The aim of this paper is to propose and designs a suitable location for a fitness centre in Batagarawa metropolis. Batagarawa city is enriched with four tertiary institutions with diverse commerce and culture but lacks the facility of a well-equipped fitness centre. The proposed fitness centre intends to be an organically sound centre that will make use of principles of organic architecture to create a new pleasant environment between man and his environments. Organic architecture is the science of designing a building within pleasant natural resources and features surrounding the environment. It is regarded as visual poetry and reinterpretation of nature’s principles; as well as embodies a settlement of person, place, and materials. Using organic architecture, the design was interlaced with the dynamic, organic and monumental features surrounding the environment. The city has inadequate/no facility that is considered organic where one can keep fit in a friendly, conducive and adequate location. Thus, the need for establishing a fitness centre to cater for this need cannot be over-emphasised. Conclusively, a fitness centre will be an added advantage to this fast growing centre of learning.

Keywords: organic architecture, fitness center, environment, natural resources, natural features, building design

Procedia PDF Downloads 414
16738 Softening Finishing: Teaching and Learning Materials

Authors: C.W. Kan

Abstract:

Softening applied on textile products based on several reasons. First, the synthetic detergent removes natural oils and waxes, thus lose the softness. Second, compensate the harsh handle of resin finishing. Also, imitate natural fibres and improve the comfort of fabric are the reasons to apply softening. There are different types of softeners for softening finishing of textiles, nonionic softener, anionic softener, cationic softener and silicone softener. The aim of this study is to illustrate the proper application of different softeners and their final softening effect in textiles. The results could also provide guidance note to the students in learning this topic. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: learning materials, softening, textiles, effect

Procedia PDF Downloads 218