Search results for: life-long learning for sustainable development

Authors: Enrique Barra, Aldo Gordillo, Juan Quemada

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This paper presents the Virtual Science Hub platform. It is an open source platform that combines a social network, an e-learning authoring tool, a video conference service and a learning object repository for science teaching enrichment. These four main functionalities fit very well together. The platform was released in April 2012 and since then it has not stopped growing. Finally we present the results of the surveys conducted and the statistics gathered to validate this approach.

Keywords: e-learning, platform, authoring tool, science teaching, educational sciences

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Authors: Menuka Maharjan

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In the name of food security, agriculture intensification through conventional farming is being implemented in Nepal. Government focus on increasing agriculture production completely ignores soil as well human health. This leads to create serious soil degradation, i.e., reduction of soil fertility and microbial activity and health hazard in the country. On this note, organic farming is sustainable agriculture approach which can address challenge of sustaining food security while protecting the environment. This creates a win-win situation both for people and the environment. However, people have limited knowledge on significance of organic farming for environment conservation and food security especially developing countries like Nepal. Thus, the objective of the study was to assess the impacts of organic farming on soil fertility and microbial activity compared to conventional farming and forest in Chitwan, Nepal. Total soil organic carbon (C) was highest in organic farming (24 mg C g⁻¹ soil) followed by conventional farming (15 mg C g⁻¹ soil) and forest (9 mg C g⁻¹ soil) in the topsoil layer (0-10 cm depth). A similar trend was found for total nitrogen (N) content in all three land uses with organic farming soil possessing the highest total N content in both 0-10 cm and 10-20 cm depth. Microbial biomass C and N were also highest under organic farming, especially in the topsoil layer (350 and 46 mg g⁻¹ soil, respectively). Similarly, microbial biomass phosphorus (P) was higher (3.6 and 1.0 mg P kg⁻¹ at 0-10 and 10-20 cm depth, respectively) in organic farming compared to conventional farming and forest at both depths. However, conventional farming and forest soils had similar microbial biomass (C, N, and P) content. After conversion of forest, the P stock significantly increased by 373% and 170% in soil under organic farming at 0-10 and 10-20 cm depth, respectively. In conventional farming, the P stock increased by 64% and 36% at 0-10 cm and 10-20 cm depth, respectively, compared to forest. Overall, organic farming practices, i.e., crop rotation, residue input and farmyard manure application, significantly alters soil fertility and microbial activity. Organic farming system is emerging as a sustainable land use system which can address the issues of food security and environment conservation by increasing sustainable agriculture production and carbon sequestration, respectively, supporting to achieve goals of sustainable development.

Keywords: organic farming, soil fertility, micobial biomas, food security

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Authors: Hachmi Toifane, Pierre Tittelein, Anh Dung Tran Le, Laurent Zalewsi

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This study introduces a composite material composed of bio-sourced phase-change material (PCM) of plant origin combined with hemp shives, developed in response to environmental challenges in the construction sector. The state of the art emphasizes the low thermal storage capacity of bio-based materials and highlights increasing need for developing sustainable materials that offer optimal thermal, mechanical, and hydric performances. The combining of PCM's thermal properties and hygric properties of hemp shives results in a material that combines lightness, strength, and hygrothermal regulation. Various formulations are being assessed and compared to conventional hemp concrete. Thermal characterization includes the measurements of thermal conductivity and numerical simulations to evaluate the thermal storage capacity. The results indicate that the addition of PCM significantly enhances the material's thermal storage capacity, positioning this one as a promising, eco-friendly solution for sustainable construction and for improving the energy efficiency of buildings.

Keywords: hemp composite, bio-sourced phase change material, thermal storage, hemp shives

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Authors: Jurijs Salijevs, Katrina Bolocko

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The integration of artificial intelligence and neural networks has significantly changed full-body imaging and high-resolution 3D mapping systems, and this paper reviews research in these areas. With an emphasis on their use in the early identification of melanoma and other disorders, the goal is to give a wide perspective on the current status and potential future of these medical imaging technologies. Authors also examine methodologies such as machine learning and deep learning, seeking to identify efficient procedures that enhance diagnostic capabilities through the analysis of 3D body scans. This work aims to encourage further research and technological development to harness the full potential of AI in disease diagnosis.

Keywords: artificial intelligence, neural networks, 3D scan, body scan, 3D mapping system, healthcare

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Authors: Wang Xiu Xiu

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The professional development of engineering teachers in universities is the key to the construction of outstanding engineers in China, which is related to the quality and prospects of the entire engineering education. This study investigated 2789 teachers' professional development in different regions of China， which outlines the current situation of the professional development of engineering teachers from three perspectives: professional development needs, professional development methods and professional development effects. Data results show that engineering teachers have the strongest demand for the improvement of subject knowledge and teaching ability. Engineering faculty with 0-5 years of teaching experience, under 35 years of age and a doctorate degree have the strongest demand for development. The frequency of engineering teachers' participation in various professional development activities is low, especially in school-enterprise cooperation-related activities. There are significant differences in the participation frequency of professional development activities among engineering faculty with different teaching ages, ages, professional titles, degrees and administrative positions in schools. The professional development of engineering faculty has been improved to a certain extent and is positively affected by professional development needs and participation in professional development. In this regard, we can constantly improve the professional development system of engineering teachers from three aspects: training on demand, stimulating motivation, and optimizing resource allocation, to enhance the professional development level of engineering teachers.

Keywords: engineering teachers in universities, professional development, status quo, countermeasures

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Authors: Samar Alarif

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Smart sustainable educational campuses are the latest paradigm of innovation in the education domain. Campuses become a hub for sustainable environmental innovations. University has a vital role in paving the road for digital transformations in the infrastructure domain by preparing skilled engineers and specialists. The open digital platform enables smart campuses to simulate real education experience by managing their infrastructure within the curriculums. Moreover, it allows the engagement between governments, businesses, and citizens to push for innovation and sustainable services. Urban and building information modeling platforms have recently attained widespread attention in smart campuses due to their applications and benefits for creating the campus's digital twin in the form of an open digital platform. Qualitative and quantitative strategies were used in directing this research to develop and validate the UIM/BIM platform benefits for smart campuses FM and its impact on the institution's sustainable vision. The research findings are based on literature reviews and case studies of the TU berlin El-Gouna campus. Textual data will be collected using semi-structured interviews with actors, secondary data like BIM course student projects, documents, and publications related to the campus actors. The study results indicated that UIM/BIM has several benefits for the smart campus. Universities can achieve better capacity-building by integrating all the actors in the UIM/BIM process. Universities would achieve their community outreach vision by launching an online outreach of UIM/BIM course for the academic and professional community. The UIM/BIM training courses would integrate students from different disciplines and alumni graduated as well as engineers and planners and technicians. Open platforms enable universities to build a partnership with the industry; companies should be involved in the development of BIM technology courses. The collaboration between academia and the industry would fix the gap, promote the academic courses to reply to the professional requirements, and transfer the industry's academic innovations. In addition to that, the collaboration between academia, industry, government vocational and training centers, and civil society should be promoted by co-creation workshops, a series of seminars, and conferences. These co-creation activities target the capacity buildings and build governmental strategies and policies to support expanding the sustainable innovations and to agree on the expected role of all the stakeholders to support the transformation.

Keywords: smart city, smart educational campus, UIM, urban platforms, sustainable campus

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Authors: Suriyani Ariffin, Nor Aziah Alias, Khairil Iskandar Othman, Haslinda Yusoff

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An Integrated Cumulative Grade Point Average (iCGPA) is a mechanism and strategy to ensure the curriculum of an academic programme is constructively aligned to the expected learning outcomes and student performance based on the attainment of those learning outcomes that is reported objectively in a spider web. Much effort and time has been spent to develop a viable mechanism and trains academics to utilize the platform for reporting. The question is: How well do learners conceive the idea of their achievement via iCGPA and whether quality learner attributes have been nurtured through the iCGPA mechanism? This paper presents the architecture of an integrated CGPA mechanism purported to address a holistic evaluation from the evaluation of courses learning outcomes to aligned programme learning outcomes attainment. The paper then discusses the students’ understanding of the mechanism and evaluation of their achievement from the generated spider web. A set of questionnaires were distributed to a group of students with iCGPA reporting and frequency analysis was used to compare the perspectives of students on their performance. In addition, the questionnaire also explored how they conceive the idea of an integrated, holistic reporting and how it generates their motivation to improve. The iCGPA group was found to be receptive to what they have achieved throughout their study period. They agreed that the achievement level generated from their spider web allows them to develop intervention and enhance the programme learning outcomes before they graduate.

Keywords: learning outcomes attainment, iCGPA, programme learning outcomes, spider web, iCGPA reporting skills

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Authors: Badoiu Mihaela Catalina

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Main focus of COHESION policy was reducing social and economic disparities between member states and regions, sustainable development and equal opportunities. In this perspective, the present study intend to analyze the evolution of the European architecture and its direct impact over the real convergence in the member states.

Keywords: cooperation, European union, member states, cohesion policy

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Authors: Guanghua Zhang, Fubao Wang, Weijun Duan

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Convolution neural network (CNN) has attracted more and more attention on recent years. Especially in the field of computer vision and image classification. However, unsupervised learning with CNN has received less attention than supervised learning. In this work, we use a new powerful tool which is deep convolutional generative adversarial networks (DCGANs) to generate images from Sloan Digital Sky Survey. Training by various star and galaxy images, it shows that both the generator and the discriminator are good for unsupervised learning. In this paper, we also took several experiments to choose the best value for hyper-parameters and which could help to stabilize the training process and promise a good quality of the output.

Keywords: convolution neural network, discriminator, generator, unsupervised learning

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Authors: Jun Ming Moey, Zhiyaun Chen, David Nicholson

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Bad actors are often hard to detect in data that imprints their behaviour patterns because they are comparatively rare events embedded in non-bad actor data. An unsupervised machine learning framework is applied here to detect bad actors in financial crime datasets that record millions of transactions undertaken by hundreds of actors (<0.01% bad). Specifically, the framework combines ‘shallow’ (PCA, Isolation Forest) and ‘deep’ (Autoencoder) methods to detect outlier patterns. Detection performance analysis for both the individual methods and their combination is reported.

Keywords: detection, machine learning, deep learning, unsupervised, outlier analysis, data science, fraud, financial crime

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Authors: Kumiko Inagaki

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In recent, years, Japanese universities have begun to face a dilemma: more than half of all high school graduates go on to attend an institution of higher learning, overwhelming Japanese universities accustomed to small student bodies. These universities have been forced to embrace qualitative changes to accommodate the increased number and diversity of students who enter their establishments, students who differ in their motivations for learning, their levels of eagerness to learn, and their perspectives on the future. One of these changes is an increase in awareness among Japanese educators of the importance of active learning, which deepens students’ understanding of course material through a range of activities, including writing, speaking, thinking, and presenting, in addition to conventional “passive learning” methods such as listening to a one-way lecture. 　The purpose of this study is to examine the effectiveness of the teaching method adapted to improve active learning. A teaching method designed to promote active learning was implemented in a social science course at one of the most popular universities in Japan. A questionnaire using a five-point response format was given to students in 2,305 courses throughout the university to evaluate the effectiveness of the method based on the following measures: ① the ratio of students who were motivated to attend the classes, ② the rate at which students learned new information, and ③ the teaching method adopted in the classes. The results of this study show that the percentage of students who attended the active learning course eagerly, and the rate of new knowledge acquired through the course, both exceeded the average for the university, the department, and the subject area of social science. In addition, there are strong correlations between teaching method and student motivation and between teaching method and knowledge acquisition rate. These results indicate that the active learning teaching method was effectively implemented and that it may improve student eagerness to attend class and motivation to learn.

Keywords: active learning, Japanese university, teaching method, university education

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Authors: Gholamreza Namavar, Ali Bayati

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Nowadays according to increasing the population all around the world, consuming of fossil fuels increased dramatically. Many believe that most of the atmospheric pollution comes by using fossil fuels. The process of natural sources entering cities show one of the large challenges in consumption sources management. Nowadays, everyone considered about the consumption of fossil fuels and also reduction of consumption civil energy in megacities that play a key role in solving serious problems such as air pollution, producing greenhouse gasses, global warming and damage ozone layer. In construction industry we should use the materials with the lowest need to energy for making and carrying them, and also the materials which need the lowest energy and expenses to recycling. In this way, the kind of usage material, the way of processing, regional materials and the adaption with environment is critical. Otherwise, the isolation should be use and mention in long term. Accordingly, in this article we investigates the new ways in order to reduce environmental pollution and save more energy by using materials that are not harmful to the environment, fully insulated materials in buildings, sustainable and diversified buildings, suitable urban design and using solar energy more efficiently in order to reduce energy consumption.

Keywords: architectural design, insulation, sustainable construction, reducing energy consumption

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Authors: Vineesh Amin, Ananya Agrawal

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In a prolonged period of uncertainty and disruptions in the pre-said normal order, non-cognitive skills, especially entrepreneurial mindsets, have become a pillar that can reform the educational models to inform the economy. Dreamverse Learning Lab’s IVR-based storytelling program -Call-a-Kahaani- is an evolving experiment with an aim to kindle entrepreneurial mindsets in the remotest locations of India in an accessible and engaging manner. At the heart of this experiment is the belief that at every phase in our life’s story, we have a choice which brings us closer to achieving our true potential. This interactive program is thus designed using real-time storytelling principles to empower learners, ages 24 and below, to make choices and take decisions as they become more self-aware, practice grit, try new things through stories, guided activities, and interactions, simply over a phone call. This research paper highlights the framework behind an ongoing scalable, data-oriented, low-tech program to kindle entrepreneurial mindsets in media dark zones supported by iterative design and prototyping to reach 13700+ unique learners who made 59000+ calls for 183900+min listening duration to listen to content pieces of around 3 to 4 min, with the last monitored (March 2022) record of 34% serious listenership, within one and a half years of its inception. The paper provides an in-depth account of the technical development, content creation, learning, and assessment frameworks, as well as mobilization models which have been leveraged to build this end-to-end system.

Keywords: non-cognitive skills, entrepreneurial mindsets, speech interface, remote learning, storytelling

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Authors: M. Roberts Masillamani

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There is a phenomenal difference, as regard to the teaching methodology adopted at the urban and the rural area colleges. However, bright and talented student may be from rural back ground even. But there is huge dearth of the digitization in the rural areas and lesser developed countries. Today’s students need new skills to compete and successful in the future. Education should be combination of practical, intellectual, and social skills. What does this mean for rural classrooms and how can it be achieved. Rural colleges are not able to hire the best resources, since the best teacher’s aim is to move towards the city. If city is provided everywhere, then there will be no rural area. This is possible by forming university clusters (UC). The University cluster is a group of renowned and accredited universities coming together to bridge this dearth. The UC will deliver the live lectures and allow the students’ from remote areas to actively participate in the classroom. This paper tries to present a plan of action of providing a better live classroom teaching and learning system from the city to the rural and the lesser developed countries. This paper titled “University Clusters using ICT for teaching and learning” provides a true concept of opening live digital classroom windows for rural colleges, where resources are not available, thus reducing the digital divide. This is different from pod casting a lecture or distance learning and eLearning. The live lecture can be streamed through digital equipment to another classroom. The rural students can collaborate with their peers and critiques, be assessed, collect information, acquire different techniques in assessment and learning process. This system will benefit rural students and teachers and develop socio economic status. This will also will increase the degree of confidence of the Rural students and teachers. Thus bringing about the concept of ‘Train the Trainee’ in reality. An educational university cloud for each cluster will be built remote infrastructure facilities (RIF) for the above program. The users may be informed, about the available lecture schedules, through the RIF service. RIF with an educational cloud can be set by the universities under one cluster. This paper talks a little more about University clusters and the methodology to be adopted as well as some extended features like, tutorial classes, library grids, remote laboratory login, research and development.

Keywords: lesser developed countries, digital divide, digital learning, education, e-learning, ICT, library grids, live classroom windows, RIF, rural, university clusters and urban

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Authors: R Palson Kennedy, P.Kiran Sai

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This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

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Authors: Erhan Eroğlu

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This paper presents a new method called Mentor and Mentee Based Learning. This new method is becoming more and more common especially at workplaces. This study is significant as it clearly underlines how it works well. Education has always aimed at equipping people with the necessary knowledge and information. For many decades it went on teachers’ talk and chalk methods. In the second half of the nineteenth century educators felt the need for some changes in delivery systems. Some new terms like self- discovery, learner engagement, student centered learning, hands on learning have become more and more popular for such a long time. However, some educators believe that there is much room for better learning methods in many fields as they think the learners still cannot fulfill their potential capacities. Thus, new systems and methods are still being developed and applied at education centers and work places. One of the latest methods is assigning some mentors for the newly recruited employees and training them within a mentor and mentee program which allows both parties to see their strengths and weaknesses and the areas which can be improved. This paper aims at finding out the perceptions of the mentors and mentees on the programs they are offered at their workplaces and suggests some betterment alternatives. The study has been conducted via a qualitative method whereby some interviews have been done with both mentors and mentees separately and together. Results show that it is a great way to train inexperienced one and also to refresh the older ones. Some points to be improved have also been underlined. The paper shows that education is not a one way path to follow.

Keywords: learning, mentor, mentee, training

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Authors: Arup Saha Chaudhuri

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Structural steel is a very ductile material with high strength carrying capacity, thus it is very useful to make earthquake resistant buildings. It is a homogeneous material also. The member section and the structural system can be made very efficient for economical design. As the steel is recyclable and reused, it is a green material. The embodied energy for the efficiently designed steel structure is less than the RC structure. For sustainable green building steel is the best material nowadays. Moreover, pre-engineered and pre-fabricated faster construction methodologies help the development work to complete within the stipulated time. In this paper, the usefulness of Eccentric Bracing Frame (EBF) in steel structure over Moment Resisting Frame (MRF) and Concentric Bracing Frame (CBF) is shown. Stability of the steel structures against horizontal forces especially in seismic condition is efficiently possible by Eccentric bracing systems with economic connection details. The EBF is pin–ended, but the beam-column joints are designed for pin ended or for full connectivity. The EBF has several desirable features for seismic resistance. In comparison with CBF system, EBF system can be designed for appropriate stiffness and drift control. The link beam is supposed to yield in shear or flexure before initiation of yielding or buckling of the bracing member in tension or compression. The behavior of a 2-D steel frame is observed under seismic loading condition in the present paper. Ductility and brittleness of the frames are compared with respect to time period of vibration and dynamic base shear. It is observed that the EBF system is better than MRF system comparing the time period of vibration and base shear participation.

Keywords: steel building, green and sustainable, earthquake resistant, EBF system

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Authors: Tanmay Bisen, Aastha Shayla

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This study introduces an advanced approach to tree canopy detection in urban environments and a regional analysis of Northern and Central Kolkata that delves into the intricate relationship between urban development and environmental conservation. Leveraging high-resolution drone imagery from diverse urban green spaces in Kolkata, we fine-tuned the deep forest model to enhance its precision and accuracy. Our results, characterized by an impressive Intersection over Union (IoU) score of 0.90 and a mean average precision (mAP) of 0.87, underscore the model's robustness in detecting and classifying tree crowns amidst the complexities of aerial imagery. This research not only emphasizes the importance of model customization for specific datasets but also highlights the potential of drone-based remote sensing in urban forestry studies. The study investigates the spatial distribution, density, and environmental impact of trees in Northern and Central Kolkata. The findings underscore the significance of urban green spaces in met-ropolitan cities, emphasizing the need for sustainable urban planning that integrates green infrastructure for ecological balance and human well-being.

Keywords: urban greenery, advanced spatial distribution analysis, drone imagery, deep learning, tree detection

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Authors: Lydia Nkechi Philip

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Due to its well-documented commitment to sustainability across diverse global markets, Unilever, a multinational consumer goods powerhouse, serves as a compelling case study. The study's goal is to critically examine Unilever's CSR initiatives, assessing their alignment with international standards and the impact on consumer perceptions and loyalty. The study investigates how Unilever's CSR practices resonate with consumers in various regions using a mixed-methods approach that includes surveys and interviews. The conceptual framework considers the role of sustainable marketing practices as a bridge builder in the CSR-consumer relationship. The findings are expected to provide valuable insights for businesses seeking to navigate the complex terrain of global markets while remaining ethical and sustainable. As consumers place a higher value on socially responsible brands, this study examines Unilever's CSR impact on consumer behavior. The abstract captures the essence of the study, providing a sneak peek at the methodology, key objectives, and anticipated contributions to our understanding of CSR's role in shaping consumer attitudes and loyalty in the global marketplace.

Keywords: Unilever, consumer loyalty, sustainable marketing practices, consumer loyalties

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

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Authors: Manuela Nayantara Jeyaraj

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Having moved into the 21^st century, it is way past being arguable that innovative technology needs to be incorporated into conventional classroom teaching. Though the Western world has found presumable success in achieving this, it is still a concept under battle in developing countries such as Sri Lanka. Reaching the acme of implementing interactive virtual learning within classrooms is a struggling idealistic fascination within the island. In order to overcome this problem, this study is set to reveal facts that limit the implementation of virtual, interactive learning within the school classrooms and provide hacks that could prove the augmented use of the Virtual World to enhance teaching and learning experiences. As each classroom moves along with the usage of technology to fulfill its functionalities, a few intense hacks provided will build the administrative onuses on a virtual system. These hacks may divulge barriers based on social conventions, financial boundaries, digital literacy, intellectual capacity of the staff, and highlight the impediments in introducing students to an interactive virtual learning environment and thereby provide the necessary actions or changes to be made to succeed and march along in creating an intellectual society built on virtual learning and lifestyle. This digital learning environment will be composed of multimedia presentations, trivia and pop quizzes conducted on a GUI, assessments conducted via a virtual system, records maintained on a database, etc. The ultimate objective of this study could enhance every child's basic learning environment; hence, diminishing the digital divide that exists in certain communities.

Keywords: digital divide, digital learning, digitization, Sri Lanka, teaching methodologies

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Authors: Bandhan Dey, Muhsina Bintoon Yiasha, Gulam Sulaman Choudhury

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Chest disease is one of the most problematic ailments in our regular life. There are many known chest diseases out there. Diagnosing them correctly plays a vital role in the process of treatment. There are many methods available explicitly developed for different chest diseases. But the most common approach for diagnosing these diseases is through X-ray. In this paper, we proposed a multi-classification deep learning model for diagnosing COVID-19, lung cancer, pneumonia, tuberculosis, and atelectasis from chest X-rays. In the present work, we used the transfer learning method for better accuracy and fast training phase. The performance of three architectures is considered: InceptionV3, VGG-16, and VGG-19. We evaluated these deep learning architectures using public digital chest x-ray datasets with six classes (i.e., COVID-19, lung cancer, pneumonia, tuberculosis, atelectasis, and normal). The experiments are conducted on six-classification, and we found that VGG16 outperforms other proposed models with an accuracy of 95%.

Keywords: deep learning, image classification, X-ray images, Tensorflow, Keras, chest diseases, convolutional neural networks, multi-classification

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Authors: Menoka Bal, David Bryde

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Sustainability in supply chain has become a topic of great interest and is linked to the assumption that a more sustainable the supply chain is the more the supply chain can perform better. The aim of this paper is to identify the different key aspects of the sustainable supply chain management. This paper will also identify the practices that are required to fulfill the demands of sustainability and, therefore, contributing to improve the sustainability performance. As part of this, the authors will identify how these different practices of implementing to achieve Sustainability in Supply Chain. This paper is conceptual in nature. This paper identifies some of the key categories which are of high importance for the sustainable management of supply chains. These key categories are: Managing the Supply Chain Risk, Improving the Supply Chain Performance, Managing the Supply Chain Value, Making the Supply Chain Leaner, Managing the Supply Chain Relationship. Through in-depth analysis, this paper aims to develop a theory of integrated management process that is most appropriate for sustainability assessment in supply chain.

Keywords: sustainability, risk management, value management, project performance, supply chain management

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Authors: Shiao-Wei Chu

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In order to enhance the ability of their graduates to compete in an increasingly globalized economy, the majority of universities in Taiwan require students to pass Freshman English in order to earn a bachelor's degree. However, many college students show low motivation in English class for several important reasons, including exam-oriented lessons, unengaging classroom activities, a lack of opportunities to use English in authentic contexts, and low levels of confidence in using English. Students’ lack of motivation in English classes is evidenced when students doze off, work on assignments from other classes, or use their phones to chat with others, play video games or watch online shows. Cooperative learning aims to address these problems by encouraging language learners to use the target language to share individual experiences, cooperatively complete tasks, and to build a supportive classroom learning community whereby students take responsibility for one another’s learning. This study includes approximately 50 student participants in a low-proficiency Freshman English class. Each week, participants will work together in groups of between 3 and 4 students to complete various in-class interactive tasks. The instructor will employ a reward system that incentivizes students to be responsible for their own as well as their group mates’ learning. The rewards will be based on points that team members earn through formal assessment scores as well as assessment of their participation in weekly in-class discussions. The instructor will record each team’s week-by-week improvement. Once a team meets or exceeds its own earlier performance, the team’s members will each receive a reward from the instructor. This cooperative learning approach aims to stimulate EFL freshmen’s learning motivation by creating a supportive, low-pressure learning environment that is meant to build learners’ self-confidence. Students will practice all four language skills; however, the present study focuses primarily on the learners’ reading comprehension. Data sources include in-class discussion notes, instructor field notes, one-on-one interviews, students’ midterm and final written reflections, and reading scores. Triangulation is used to determine themes and concerns, and an instructor-colleague analyzes the qualitative data to build interrater reliability. Findings are presented through the researcher’s detailed description. The instructor-researcher has developed this approach in the classroom over several terms, and its apparent success at motivating students inspires this research. The aims of this study are twofold: first, to examine the possible benefits of this cooperative approach in terms of students’ learning outcomes; and second, to help other educators to adapt a more cooperative approach to their classrooms.

Keywords: freshman English, cooperative language learning, EFL learners, learning motivation, zone of proximal development

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Authors: Marilei Amadeu Sabino

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

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

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Authors: Jeremiah Mutamba

Abstract:

Water is a critical resource for sustainable economic growth and social development. It enables societies to thrive and influences every urban center’s future. Thus, water must always be available in the right quantity and quality. However, in South Africa - a known physically water scarce nation – the future of sustainable urban supply of water may be in jeopardy. The country facing a water crisis influenced by insufficient infrastructure investment and maintenance, recurrent droughts and climate variation, human induced water quality deterioration, as well as growing lack of technical capacity in water institutions, particularly local municipalities. Aside of the eight metropolitan municipalities for the country, most municipalities struggle with provision of reliable water to their citizens. These municipalities contend with having now capable engineers, aging infrastructure with concomitant high system water losses (of 30% and upwards), coupled with growing water demand from expanding industries and population growth. Also, a significant portion (44%) of national water treatment plants are in critically poor condition, requiring urgent rehabilitation. Municipalities also struggle to raise funding to instate projects. All these factors militate against sustainable urban water supply in the country. Urgent mitigation measures are required. This paper seeks to review the extent of the current water supply challenges in South Africa’s urban centers, including searching for practical and cost-effective measures. The study followed a qualitative approach, combining desktop literature research, interviews with key sector stakeholders, and a workshop. Phenomenological data analysis technique was used to study and examine interview data and secondary desktop data. Preliminary findings established the building of technical or engineering capacity, reversal of the high physical water losses, rehabilitation of poor condition and dysfunctional water treatment works, diversification of water resource mix, and water scarcity awareness programs as possible practical solutions. Other proposed solutions include the use of performance-based or value-based contracting to fund initiatives to reduce high system water losses. Out-come based arrangements for revenue increasing water loss reduction projects were considered more practical in funding-stressed local municipalities. If proactively implemented in an integrated manner, these proposed solutions are likely to ensure sustainable urban water supply in South African urban centers in the future.

Keywords: sustainable, water scarcity, water supply, South Africa

Procedia PDF Downloads 123

Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan

Abstract:

A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.

Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection

Procedia PDF Downloads 125

Authors: Chiou-Shiue Ko, Pei-Fang Wu, Shu-hsien Tseng

Abstract:

The researchers adopted two-year action research to investigate the professional collaborative process and development in learning communities for both early childhood and early childhood special education teachers on implementing the children’s school success curriculum framework. The participating teachers were recruited from three preschool sites for this current study. Research data were collected from multiple methods in order to ensure the data quality and validity. The results showed that participating educators had achieved professional growth, and they became more aware of teaching intentions and the preparation for the curriculum. Teachers in this research become more child-focused in teaching and create opportunities for children to participate in classroom activities and routines. The researcher also finds teachers’ participation levels were driven by each individual personality; during professional growth, some teachers are more proactive and reflective, and some are not. According to the research findings, suggestions for future studies and practices are provided.

Keywords: children’s school success curriculum framework, early childhood special education, preschool education, professional learning community

Procedia PDF Downloads 143

Authors: Jaeseo Lim, Jooyong Park

Abstract:

Although there is ample evidence that student involvement enhances learning, college education is still mainly centered on lectures. However, in recent years, the effectiveness of discussions and the use of collective intelligence have attracted considerable attention. This study intends to examine the empirical effects of discussions on learning outcomes in various conditions. Eighty eight college students participated in the study and were randomly assigned to three groups. Group 1 was told to review material after a lecture, as in a traditional lecture-centered class. Students were given time to review the material for themselves after watching the lecture in a video clip. Group 2 participated in a discussion in groups of three or four after watching the lecture. Group 3 participated in a discussion after studying on their own. Unlike the previous two groups, students in Group 3 did not watch the lecture. The participants in the three groups were tested after studying. The test questions consisted of memorization problems, comprehension problems, and application problems. The results showed that the groups where students participated in discussions had significantly higher test scores. Moreover, the group where students studied on their own did better than that where students watched a lecture. Thus discussions are shown to be effective for enhancing learning. In particular, discussions seem to play a role in preparing students to solve application problems. This is a preliminary study and other age groups and various academic subjects need to be examined in order to generalize these findings. We also plan to investigate what kind of support is needed to facilitate discussions.

Keywords: discussions, education, learning, lecture, test

Procedia PDF Downloads 176

Authors: Michael Stewart

Abstract:

Mutation testing is a type of software testing proposed in the 1970s where program statements are deliberately changed to introduce simple errors so that test cases can be validated to determine if they can detect the errors. Test cases are executed against the mutant code to determine if one fails, detects the error and ensures the program is correct. One major issue with this type of testing was it became intensive computationally to generate and test all possible mutations for complex programs. This paper used reinforcement learning and parallel processing within the context of mutation testing for the selection of mutation operators and test cases that reduced the computational cost of testing and improved test suite effectiveness. Experiments were conducted using sample programs to determine how well the reinforcement learning-based algorithm performed with one live mutation, multiple live mutations and no live mutations. The experiments, measured by mutation score, were used to update the algorithm and improved accuracy for predictions. The performance was then evaluated on multiple processor computers. With reinforcement learning, the mutation operators utilized were reduced by 50 – 100%.

Keywords: automated-testing, machine learning, mutation testing, parallel processing, reinforcement learning, software engineering, software testing

Procedia PDF Downloads 198