Search results for: online learning management system

Authors: Kwok Tak Kit

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Combating climate change is becoming a hot topic in various sectors. Building construction and infrastructure sectors contributed a significant proportion of waste and GHGs emissions in the economy of different countries and cities. Many types of research had conducted and discussed the topic of waste management and waste management being a macro-level control is well developed in the building and construction industry. However, there is little research and studies on the micro-level of waste management, “building construction material wastage management,” and fewer reviews about regulatory control in the building construction sector. In this paper, we will focus on the potentialities and importance of material wastage management and review the deficiencies of the current standard to take into account the reduction of material wastage in a systematic and quantitative approach.

Keywords: quantitative measurement, material wastage management plan, waste management, uncalculated waste, circular economy

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Authors: Robert Caulk

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A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

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Authors: Amah Nnachi Lofty, Oyefeso Olufemi, Ibiam Udu Ama

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New and more powerful communications technologies continue to emerge at a rapid pace and their uses in education are widespread and the impact remarkable in the developing societies. This study investigates Mobile Collaboration Learning Technique (MCLT) on learners’ outcome among students in tertiary institutions of developing nations (a case of Nigeria students). It examines the significance of retention achievement scores of students taught using mobile collaboration and conventional method. The sample consisted of 120 students using Stratified random sampling method. Three research questions and hypotheses were formulated, and tested at a 0.05 level of significance. A student achievement test (SAT) was made of 40 items of multiple-choice objective type, developed and validated for data collection by professionals. The SAT was administered to students as pre-test and post-test. The data were analyzed using t-test statistic to test the hypotheses. The result indicated that students taught using MCLT performed significantly better than their counterparts using the conventional method of instruction. Also, there was no significant difference in the post-test performance scores of male and female students taught using MCLT. Based on the findings, the following recommendations was made that: Mobile collaboration system be encouraged in the institutions to boost knowledge sharing among learners, workshop and trainings should be organized to train teachers on the use of this technique and that schools and government should formulate policies and procedures towards responsible use of MCLT.

Keywords: education, communication, learning, mobile collaboration, technology

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Authors: Salah Kayed Kayed, Jessica Hong Yang

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This study investigates, whether earnings management in the audited financial statements is associated with tone management in the narrative sections of the annual report in the UK. Earnings management and narrative disclosure are communication strategies used from managers to communicate with investors or other users. Because earnings management and narrative disclosure stem from managers, they can exploit this by doing manipulation in their earnings, and simultaneously disclosing qualitative text (narrative information) in their reports as a tone of words, which will affect users’ perception, and hence users will be misinformed. The association between earnings and tone management can be explained by the self-serving, through cognitive reference points, theory. The sample period lasts from 2010 to 2015, and the sample comprises all non-financial firms that consider under FTSE 350 in any year during the sample period. A list of words from previous research is used to measure the tone in the narrative sections of the annual report. Because this study focuses on the managerial strategic choice and the subjective issues that come from management, it uses the abnormal tone to capture the managerial discretion on tone, and a number of different discretionary accruals proxies to measure earnings management, where accruals management is considered as a manipulation tool from managers to change the users' perception. This research is motivated to fulfil the literature gap by examining the association between earnings and tone management. Moreover, if firms that apply earnings management use tone management to mislead investors, it is beneficial for investors, policy makers, standard setters, or other users to know whether there is an association between earnings management and tone management. Clearly, we believe that this study is fundamental in the accounting context, where it evaluates the communication strategies that are used in firms' financial reports. Consistent with prior research, it is expected that tone management is positively associated with earnings management. This means that firms that use earnings management have incentives to manipulate in their narrative disclosure through tone of words, to reflect a good perception for users, which will conceal the earnings management techniques used in their reporting.

Keywords: earnings management, FTSE 350, narrative disclosure, tone management

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Authors: Morakinyo Akintolu, Moeketsi Letseka

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In the year 2015, the United Nation member states, through the representative of all heads of states present, adopted the 17 Global goals known as the Sustainable Development Goals in their capacity to bring about social, economic, and cultural development to the world. Therefore, the need to accommodate equitable development one of the major goals is to achieve equitable and quality education for all to bring about international development. In this light, the study investigates the role of open distance learning in achieving sustainable development goals. Open distance learning comes as a second chance to individuals in disseminating educational content to students who missed the opportunity of attending the traditional school setting. Therefore, this study investigates if the SDGs reflect this type of learning (ODL) in creating Education for all according to the 2030 agenda by the United Nations. It further ascertains the role of ODL in achieving SDGs, the challenges encountered as well as the way forward.

Keywords: open distance learning, sustainable development goals, distance education, achieving, 2030 agenda

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Authors: Kathy Gibbs

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There is a paucity of research in Australia about educators’ use of differentiated instruction (DI) to support the learning of students with ADHD. This study reports on small-scale, qualitative research using interviews with teachers and school leaders to identify how they use DI as an effective teaching instruction for students with ADHD. Findings showed that teachers and school leaders have a good understanding of ADHD; teachers use DI as an effective teaching practice to enhance learning for this student group and ensure the classroom environment is safe and secure. However, they do not adjust assessments for students with ADHD. School leaders are not clear on how teachers differentiate assessments or adapt to the classroom environment. These results highlight the need for further research at the teacher and teacher-educator level teachers to ensure teaching practices are effective in reducing unwanted behaviours that prevent students with ADHD from achieving their full academic potential.

Keywords: teachers, differentiated instruction, ADHD, student learning, educators knowledge

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Authors: Shael Brown, Reza Farivar

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Persistence diagrams capture valuable topological features of datasets that other methods cannot uncover. Still, their adoption in data pipelines has been limited due to the lack of publicly available tools in R (and python) for analyzing groups of them with machine learning and statistical inference. In an easy-to-use and scalable R package called TDApplied, we implement several applied analysis methods tailored to groups of persistence diagrams. The two main contributions of our package are comprehensiveness (most functions do not have implementations elsewhere) and speed (shown through benchmarking against other R packages). We demonstrate applications of the tools on simulated data to illustrate how easily practical analyses of any dataset can be enhanced with topological information.

Keywords: machine learning, persistence diagrams, R, statistical inference

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Authors: Slah Eddine Ben Fadhel

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Despite the development of new pedagogic methods, current teaching practices put more emphasis on the learning products than on the processes learners deploy. In school syllabi, for instance, very little time is devoted to both the explanation and analysis of strategies aimed at resolving problems by means of targeting students’ metacognitive procedures. Within a cognitive framework, teaching/learning contexts are conceived of in terms of cognitive, metacognitive and affective activities intended for the treatment of information. During these activities, learners come to develop an array of knowledge and strategies which can be subsumed within an active and constructive process. Through the investigation of strategies and metacognition concepts, the purpose is to reflect upon the modalities at the heart of the learning process and to demonstrate, similarly, the inherent significance of a cognitive approach to learning. The scope of this paper is predicated on a study where the population is a group of 76 primary school pupils who experienced difficulty with learning French. The population was divided into two groups: the first group was submitted during three months to a strategy-based training to learn French. All through this phase, the teachers centred class activities round making learners aware of the strategies the latter deployed and geared them towards appraising the steps these learners had themselves taken by means of a variety of tools, most prominent among which is the logbook. The second group was submitted to the usual learning context with no recourse whatsoever to any strategy-oriented tasks. The results of both groups point out the improvement of linguistic competences in the French language in the case of those pupils who were trained by means of strategic procedures. Furthermore, this improvement was noted in relation with the native language (Arabic), a fact that tends to highlight the importance of the interdisciplinary investigation of (meta-)cognitive strategies. These results show that strategic learning promotes in pupils the development of a better awareness of their own processes, which contributes to improving their general linguistic competences.

Keywords: constructive approach, cognitive strategies, metacognition, learning

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Authors: Qianjia Cheng, Hongquan Jiang

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Crowdsourcing solves the problems that computers can't handle by integrating computers and the Internet. Its extensive knowledge sources, high efficiency and high quality, make crowdsourcing attract wide attention in industry and academia in recent years. The development of online crowdsourcing platforms such as Clickworker and Amazon Mechanical Turk(Mturk) tend to mature gradually. This paper sorts out the concept of crowdsourcing, sorts out the workflow of competitive crowdsourcing, summarizes the related technologies of crowdsourcing based on the workflow, quality control, cost control and delay control, introduces the typical crowdsourcing platform. Finally, we highlight some open problems of the current crowdsourcing and present some future research direction in this area.

Keywords: application, crowdsourcing, crowdsourcing platform, system architecture

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Authors: Omar Alshehri, Vic Lally

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This paper examined the attitudes of using social media tools to support learning at a university in Saudi Arabia. Moreover, it investigated the students’ current usage of these tools and examined the barriers they could face during the use of social media tools in the education process. Participants in this study were 42 university students. A web-based survey was used to collect data for this study. The results indicate that all of the students were familiar with social media and had used at least one type of social media for learning. It was found out that all students had very positive attitudes towards the use of social media and welcomed using these tools as a supplementary to the curriculum. However, the results indicated that the major barriers to using these tools in learning were distraction, opposing Islamic religious teachings, privacy issues, and cyberbullying. The study recommended that this study could be replicated at other Saudi universities to investigate factors and barriers that might affect Saudi students’ attitudes toward using social media to support learning.

Keywords: barriers to social media use, benefits of social media use, higher education, Saudi Arabia, social media

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Authors: Surah Aldakhl, Dafer Alali, Mohamed Zohdy

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The next generation of electricity grid infrastructure, known as the "smart grid," integrates smart ICT (information and communication technology) into existing grids in order to alleviate the drawbacks of existing one-way grid systems. Future power systems' efficiency and dependability are anticipated to significantly increase thanks to the Smart Grid, especially given the desire for renewable energy sources. The security of the Smart Grid's cyber infrastructure is a growing concern, though, as a result of the interconnection of significant power plants through communication networks. Since cyber-attacks can destroy energy data, beginning with personal information leaking from grid members, they can result in serious incidents like huge outages and the destruction of power network infrastructure. We shall thus propose a secure smart energy management system based on the Blockchain as a remedy for this problem. The power transmission and distribution system may undergo a transformation as a result of the inclusion of optical fiber sensors and blockchain technology in smart grids. While optical fiber sensors allow real-time monitoring and management of electrical energy flow, Blockchain offers a secure platform to safeguard the smart grid against cyberattacks and unauthorized access. Additionally, this integration makes it possible to see how energy is produced, distributed, and used in real time, increasing transparency. This strategy has advantages in terms of improved security, efficiency, dependability, and flexibility in energy management. An in-depth analysis of the advantages and drawbacks of combining blockchain technology with optical fiber is provided in this paper.

Keywords: smart grids, blockchain, fiber optic sensor, security

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Authors: Samuel Olajide Babawale, Jonathan Bridge

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Natural Flood Management (NFM) is promoted as part of sustainable flood management (SFM) in response to climate change adaptation. Stakeholder engagement is central to this approach, and current trends are progressively moving towards a collaborative learning approach where stakeholder participation is perceived as one of the indicators of sustainable development. Within this methodology, participation embraces a diversity of knowledge and values underpinned by a philosophy of empowerment, equity, trust, and learning. To identify barriers to NFM uptake, there is a need for a new understanding of how stakeholder participation could be enhanced to benefit individual and community resilience within SFM. This is crucial in light of climate change threats and scientific reliability concerns. In contributing to this new understanding, this research evaluated the proposed interventions on six (6) UK NFM in a catchment known as the Sheffield Lakeland Partnership Area with reference to the Environment Agency Working with Natural Processes (WWNP) Potentials/Opportunities. Three of the opportunities, namely Run-off Attenuation Potential of 1%, Run-off Attenuation Potential of 3.3% and Riparian Woodland Potential, were modeled. In all the models, the interventions, though they have been proposed or already in place, are not in agreement with the data presented by EA WWNP. Findings show some institutional weaknesses, which are seen to inhibit the development of adequate flood management solutions locally with damaging implications for vulnerable communities. The gap in communication from practitioners poses a challenge to the implementation of real flood mitigating measures that align with the lead agency’s nationally accepted measures which are identified as not feasible by the farm management officers within this context. Findings highlight a dominant top-bottom approach to management with very minimal indication of local interactions. Current WWNP opportunities have been termed as not realistic by the people directly involved in the daily management of the farms, with less emphasis on prevention and mitigation. The targeted approach suggested by the EA WWNP is set against adaptive flood management and community development. The study explores dimensions of participation using the self-reliance and self-help approach to develop a methodology that facilitates reflections of currently institutionalized practices and the need to reshape spaces of interactions to enable empowered and meaningful participation. Stakeholder engagement and resilience planning underpin this research. The findings of the study suggest different agencies have different perspectives on “community participation”. It also shows communities in the case study area appear to be least influential, denied a real chance of discussing their situations and influencing the decisions. This is against the background that the communities are in the most productive regions, contributing massively to national food supplies. The results are discussed concerning practical implications for addressing interagency partnerships and conducting grassroots collaborations that empower local communities and seek solutions to sustainable development challenges. This study takes a critical look into the challenges and progress made locally in sustainable flood risk management and adaptation to climate change by the United Kingdom towards achieving the global 2030 agenda for sustainable development.

Keywords: natural flood management, sustainable flood management, sustainable development, working with natural processes, environment agency, run-off attenuation potential, climate change

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Authors: R. Nandhini, Gaurab Mudbhari

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Ranging from the field of health care to self-driving cars, machine learning and deep learning algorithms have revolutionized the field with the proper utilization of images and visual-oriented data. Segmentation, regression, classification, clustering, dimensionality reduction, etc., are some of the Machine Learning tasks that helped Machine Learning and Deep Learning models to become state-of-the-art models for the field where images are key datasets. Among these tasks, classification and clustering are essential but difficult because of the intricate and high-dimensional characteristics of image data. This finding examines and assesses advanced techniques in supervised classification and unsupervised clustering for image datasets, emphasizing the relative efficiency of Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), Deep Embedded Clustering (DEC), and self-supervised learning approaches. Due to the distinctive structural attributes present in images, conventional methods often fail to effectively capture spatial patterns, resulting in the development of models that utilize more advanced architectures and attention mechanisms. In image classification, we investigated both CNNs and ViTs. One of the most promising models, which is very much known for its ability to detect spatial hierarchies, is CNN, and it serves as a core model in our study. On the other hand, ViT is another model that also serves as a core model, reflecting a modern classification method that uses a self-attention mechanism which makes them more robust as this self-attention mechanism allows them to lean global dependencies in images without relying on convolutional layers. This paper evaluates the performance of these two architectures based on accuracy, precision, recall, and F1-score across different image datasets, analyzing their appropriateness for various categories of images. In the domain of clustering, we assess DEC, Variational Autoencoders (VAEs), and conventional clustering techniques like k-means, which are used on embeddings derived from CNN models. DEC, a prominent model in the field of clustering, has gained the attention of many ML engineers because of its ability to combine feature learning and clustering into a single framework and its main goal is to improve clustering quality through better feature representation. VAEs, on the other hand, are pretty well known for using latent embeddings for grouping similar images without requiring for prior label by utilizing the probabilistic clustering method.

Keywords: machine learning, deep learning, image classification, image clustering

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Authors: Ali Alattabi, Clare Harris, Rafid Alkhaddar, Ali Alzeyadi

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Petroleum refinery wastewater (PRW) can be considered as one of the most significant source of aquatic environmental pollution. It consists of oil and grease along with many other toxic organic pollutants. In recent years, a new technique was implemented using different types of membranes and sequencing batch reactors (SBRs) to treat PRW. SBR is a fill and draw type sludge system which operates in time instead of space. Many researchers have optimised SBRs’ operating conditions to obtain maximum removal of undesired wastewater pollutants. It has gained more importance mainly because of its essential flexibility in cycle time. It can handle shock loads, requires less area for operation and easy to operate. However, bulking sludge or discharging floating or settled sludge during the draw or decant phase with some SBR configurations are still one of the problems of SBR system. The main aim of this study is to develop and innovative design for the SBR optimising the process variables to result is a more robust and efficient process. Several experimental tests will be developed to determine the removal percentages of chemical oxygen demand (COD), Phenol and nitrogen compounds from synthetic PRW. Furthermore, the dissolved oxygen (DO), pH and oxidation-reduction potential (ORP) of the SBR system will be monitored online to ensure a good environment for the microorganisms to biodegrade the organic matter effectively.

Keywords: petroleum refinery wastewater, sequencing batch reactor, hydraulic retention time, Phenol, COD, mixed liquor suspended solids (MLSS)

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Authors: Sherehan Hamdalla

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Egypt has experienced a series of terrifying love crimes in the last few months. This ‘trend’ of love crimes started with a young man caught on video slaughtering his ex-girlfriend in the street in the city of El Mansoura. The crime shocked all Egyptian citizens at all levels; unfortunately, not less than three similar crimes took place in other different Egyptian cities with the same killing trigger. The characteristics and easy access and reach of social media consider the reason why it is one of the most crucial online communication channels; users utilize social media platforms for sharing and exchanging ideas, news, and many other activities; they can freely share posts that reflect their mindset or personal views regarding any issues, these posts are going viral in all social media account by reposting or numbers of shares for these posts to support the content included, or even to attack. The repetition of sharing certain posts could mobilize other supporters with the same point of view, especially when that crowd’s online participation is confronting a public opinion case’s consequences. The death of that young woman was followed by similar crimes in other cities, such as El Sharkia and Port Said. These love crimes provoked a massive wave of contention among all social classes in Egypt. Strangely, some were supporting the criminal and defending his side for several reasons, which the study will uncover. Facebook, the most popular social media platform for Egyptians, reflects the debate between supporters of the victim and supporters of the criminal. Facebook pages were created specifically to disseminate certain viewpoints online, for example, asking for the maximum penalty to be given to criminals. These pages aimed to mobilize the maximum number of supporters and to affect the outcome of the trials.

Keywords: love crimes, victim, criminal, social media

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Authors: Ashish James, Anusha James

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The impressive predictive performance of deep learning techniques on a wide range of tasks has led to its widespread use. Estimating the confidence of these predictions is paramount for improving the safety and reliability of such systems. However, the uncertainty estimates provided by neural networks (NNs) tend to be overconfident and unreasonable. Ensemble of NNs typically produce good predictions but uncertainty estimates tend to be inconsistent. Inspired by these, this paper presents a framework that can quantitatively estimate the uncertainties by leveraging the advances in transfer learning through slight modification to the existing training pipelines. This promising algorithm is developed with an intention of deployment in real world problems which already boast a good predictive performance by reusing those pretrained models. The idea is to capture the behavior of the trained NNs for the base task by augmenting it with the uncertainty estimates from a supplementary network. A series of experiments with known and unknown distributions show that the proposed approach produces well calibrated uncertainty estimates with high quality predictions.

Keywords: uncertainty estimation, neural networks, transfer learning, regression

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Authors: Yonatan Sverdlov, Shimon Ullman

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Artificial neural networks encounter a notable challenge known as continual learning, which involves acquiring knowledge of multiple tasks over an extended period. This challenge arises due to the tendency of previously learned weights to be adjusted to suit the objectives of new tasks, resulting in a phenomenon called catastrophic forgetting. Most approaches to this problem seek a balance between maximizing performance on the new tasks and minimizing the forgetting of previous tasks. In contrast, our approach attempts to maximize the performance of the new task, while ensuring zero forgetting. This is accomplished through the introduction of task-specific modulation parameters for each task, and only these parameters are learned for the new task, after a set of initial tasks have been learned. Through comprehensive experimental evaluations, our model demonstrates superior performance in acquiring and retaining novel tasks that pose difficulties for other multi-task models. This emphasizes the efficacy of our approach in preventing catastrophic forgetting while accommodating the acquisition of new tasks.

Keywords: continual learning, life-long learning, neural analogies, adaptive modulation

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Authors: Francisco A. Ribeiro Da Costa

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Who is responsible for teaching architecture; consider various ways to participate in learning, manipulating various pedagogical tools to streamline the creative process. The Architectural Design Studio (ADS) should become a holistic, systemic process responding to the complexity of our world. This essay corresponds to a deep reflection developed by the author on the teaching of architecture. The outcomes achieved are the corollary of experimentation; discussion and application of pedagogical methods that allowed consolidate the creativity applied by students. The purpose is to show the conjectures that have been considered effective in creating an intellectual environment that nurtures the subject of Architectural Design Studio (ADS), as an operational synthesis in the final stage of the degree. These assumptions, which are part of the proposed model, displaying theories and teaching methodologies that try to respect the learning process based on student learning styles Kolb, ensuring their latent specificities and formulating the structure of the ASD discipline. In addition, the assessing methods are proposed, which consider the architectural Design Studio as an operational synthesis in the teaching of architecture.

Keywords: teaching-learning, architectural design studio, architecture, education

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Authors: Kunle Oparinde

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The Covid-19 pandemic has seen several rumors and conspiracy theories overtake the truth in many online platforms across several African countries. Just as the coronavirus has travelled widely, misinformation has equally spread. Thus, it is important to launch investigations into these conspiracy theories in order to detect them early and as a result, implore health practitioners and agencies to be more proactive in repelling misinformation while at the same time provide the general populace with purely undiluted information regarding the virus. Through social media posts on platforms such as Twitter, Facebook, and WhatsApp, as well as online platforms such as Google, this study intends to draw as many instances as possible of infodemic and misinformation by reviewing and analyzing these texts and the resulting implication if the misinformation continues to gain popularity. The study discovers the use of conspiracy theories, rumors, hyperbolism, and unverified claims as elements of infodemic used during the coronavirus pandemic. Importantly, the findings of the study will assist the public to be cautious and vigilant against false information that are being peddled as original.

Keywords: infodemic, miscommunication, accuracy, social media, rumors, conspiracy

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Authors: Hitham Yami

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This study will focus primarily on assessing the availability requirements of the electronic management of oil companies in Libya, and the mean objectives of the research applying electronic management and make recommendations and steps to approach electronic management. There are limited research and statistical analysis to support electronic management in Libyan companies. The groundwork for the proposed approach is to develop independent variables and the dependent variables to be restructured after it Alntra side of the field and the side to get the data to achieve the desired results and solving the problem faced by the Libyan Oil Corporation. All these strategies are proposed to achieve the goal, and solving Libyan oil installations.

Keywords: oil company’s revenue, independent variables, electronic management, Libyan oil corporation

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Authors: Munirah Alaboudi

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This paper discusses a research project carried out with 12 first-year graduate students enrolled in research methods course prior to undertaking a graduate thesis during the academic year 2019. The research was designed for the objective of creating research methods course structure that embraces an individualized and activity-based approach to learning in a highly engaging group environment. This approach targeted innovating the traditional research methods lecture-based, theoretical format where students reported less engagement and limited learning. This study utilized action research methodology in developing a different approach to research methods course instruction where student performance indicators and feedback were periodically collected to assess the new teaching method. Student learning was achieved through utilizing the flipped classroom approach where students learned the material at home and classroom activities were designed to implement and experiment with the newly acquired information, with the guidance of the course instructor. Student learning in class was practiced through a series of activities based on different research methods. With the goal of encouraging student engagement, a wide range of activities was utilized including workshops, role play, mind-mapping, presentations, peer evaluations. Data was collected through an open-ended qualitative questionnaire to establish whether students were engaged in the material they were learning, and to what degree were they engaged, and to test their mastery level of the concepts discussed. Analysis of the data presented positive results as around 91% of the students reported feeling more engaged with the active learning experience and learning research by “actually doing research, not just reading about it”. The students expressed feeling invested in the process of their learning as they saw their research “gradually come to life” through peer learning and practice during workshops. Based on the results of this study, the research methods course structure was successfully remodeled and continues to be delivered.

Keywords: research methods, higher education instruction, flipped classroom, graduate education

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Authors: Renga Rao Krishnamoorthy, Raihan Tahir

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The quality of classroom learning and teaching delivery has been and will continue to be debated at various levels worldwide. The regional cooperation programme to improve the quality and labour market orientation of the Technical and Vocational Education and Training (RECOTVET), ‘Deutsche Gesellschaft für Internationale Zusammenarbeit’ (GIZ), in line with the sustainable development goals (SDG), has taken the initiative in the development of quality TVET in the ASEAN region by developing the Quality Toolbox for Better TVET Delivery (Quality Toolbox). This initiative aims to provide quick and practical materials to trainers, instructors, and personnel involved in education and training at an institute to shape the quality of classroom learning and teaching. The Quality Toolbox for Better TVET Delivery was developed in three stages: literature review and development, validation, and finalization. Thematic areas in the Quality Toolbox were derived from collective input of concerns and challenges raised from experts’ workshops through moderated sessions involving representatives of TVET institutes from 9 ASEAN Member States (AMS). The sessions were facilitated by professional moderators and international experts. TVET practitioners representing AMS further analysed and discussed the structure of the Quality Toolbox and content of thematic areas and outlined a set of specific requirements and recommendations. The application exercise of the Quality Toolbox was carried out by TVET institutes among ASM. Experience sharing sessions from participating ASEAN countries were conducted virtually. The findings revealed that TVET institutes use two types of approaches in shaping the quality of learning and teaching, which is ascribed to inductive or deductive, shaping of quality in learning and teaching is a non-linear process and finally, Q-tools can be adopted and adapted to shape the quality of learning and teaching at TVET institutes in the following: improvement of the institutional quality, improvement of teaching quality and improvement on the organisation of learning and teaching for students and trainers. The Quality Toolbox has good potential to be used at education and training institutes to shape quality in learning and teaching.

Keywords: AMS, GIZ, RECOTVET, quality tools

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Authors: Mostafa ‘Neo’ Mohsenvand, Mohammad Rasool Izadi, Pattie Maes

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EEG-based biometrics (user identification) has been explored on small datasets of no more than 157 subjects. Here we show that the accuracy of modern supervised methods falls rapidly as the number of users increases to a few thousand. Moreover, supervised methods require a large amount of labeled data for training which limits their applications in real-world scenarios where acquiring data for training should not take more than a few minutes. We show that using contrastive learning for pre-training, it is possible to maintain high accuracy on a dataset of 2130 subjects while only using a fraction of labels. We compare 5 different self-supervised tasks for pre-training of the encoder where our proposed method achieves the accuracy of 96.4%, improving the baseline supervised models by 22.75% and the competing self-supervised model by 3.93%. We also study the effects of the length of the signal and the number of channels on the accuracy of the user-identification models. Our results reveal that signals from temporal and frontal channels contain more identifying features compared to other channels.

Keywords: brainprint, contrastive learning, electroencephalo-gram, self-supervised learning, user identification

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Authors: Kemal Izci, Ahmet Oguz Akturk

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Learning is dependent on cognitive and physical differences as well as other differences such as ethnicity, language, and culture. Furthermore, these differences also influence how students show their learning. Assessment is an integral part of learning and teaching process and is essential for effective instruction. In order to provide effective instruction, teachers need to provide equal assessment opportunities for all students to see their learning difficulties and use them to modify instruction to aid learning. Successful assessment practices are dependent upon the knowledge and value of teachers. Therefore, in order to use assessment to assess and support diverse students learning, preservice and inservice teachers should hold an appropriate understanding of equitable assessment. In order to prepare teachers to help them support diverse student learning, as a first step, this study aims to explore how preservice teachers’ understand equitable assessment. 105 preservice science teachers studying at teacher preparation program in a large university located at Eastern part of Turkey participated in the current study. A questionnaire, preservice teachers’ reflection papers and interviews served as data sources for this study. All collected data qualitatively analyzed to develop themes that illustrate preservice science teachers’ understanding of equitable assessment. Results of the study showed that preservice teachers mostly emphasized fairness including fairness in grading and fairness in asking questions not out of covered concepts for equitable assessment. However, most of preservice teachers do not show an understanding of equity for providing equal opportunities for all students to display their understanding of related content. For some preservice teachers providing different opportunities (providing extra time for non-native speaking students) for some students seems to be unfair for other students and therefore, these kinds of refinements do not need to be used. The results of the study illustrated that preservice science teachers mostly understand equitable assessment as fairness and less highlight the role of using equitable assessment to support all student learning, which is more important in order to improve students’ achievement of science. Therefore, we recommend that more opportunities should be provided for preservice teachers engage in a more broad understanding of equitable assessment and learn how to use equitable assessment practices to aid and support all students learning trough classroom assessment.

Keywords: science teaching, equitable assessment, assessment literacy, preservice science teachers

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Authors: Heba Salem

Abstract:

This paper aims to share the researcher’s experience of using e-Portfolios as an assessment tool to follow up on students’ learning experiences and performance throughout the semester. It also aims at highlighting the importance of students’ self-reflection in the process of language learning. The paper begins by introducing the advanced media course, with its focus on listening and speaking skills, and introduces the students’ profiles. Then it explains the students’ role in the e-portfolio process as they are given the option to choose a listening text they studied throughout the semester and to choose a recorded oral production of their collection of artifacts throughout the semester. Students showcase and reflect on their progress in both listening comprehension and speaking. According to the research, re-listening to work given to them and to their production is a means of reflecting on both their progress and achievement. And choosing the work students want to showcase is a means to promote independent learning as well as self-expression. Students are encouraged to go back to the class learning outcomes in the process of choosing the work. In their reflections, students express how they met the specific learning outcome. While giving their presentations, students expressed how useful the experience of returning and going over what they covered to select one and going over their production as well. They also expressed how beneficial it was to listen to themselves and literally see their progress in both listening comprehension and speaking. Students also reported that they grasped more details from the texts than they did when first having it as an assignment, which coincided with one of the class learning outcomes. They also expressed the fact that they had more confidence speaking as well as they were able to use a variety of vocabulary and idiomatic expressions that students have accumulated. For illustration, this paper includes practical samples of students’ tasks and instructions as well as samples of their reflections. The results of students’ reflections coincide with what the research confirms about the effectiveness of the e-portfolios as a means of assessment. The employment of e-Portfolios has two-folded benefits; students are able to measure the achievement of the targeted learning outcomes, and teachers receive constructive feedback on their teaching methods.

Keywords: e-portfolios, assessment, self assessment, listening and speaking progress, foreign language, reflection, learning out comes, sharing experience

Procedia PDF Downloads 98

Authors: Michael J. Hahn

Abstract:

Docker is a powerful tool used by many companies such as PayPal, MetLife, Expedia, Visa, and many others. Docker works by bundling multiple applications, binaries, and libraries together on top of an operating system image called a container. The container runs on a Docker engine that in turn runs on top of a standard operating system. This centralization saves a lot of system resources. In this paper, we will be demonstrating how to bypass Transport Layer Security and execute remote code within Docker containers built on a base image of Alpine Linux version 3.7.0 through the use of .apk files due to flaws in the Alpine Linux package management program. This exploit renders any applications built using Docker with a base image of Alpine Linux vulnerable to unwanted outside forces.

Keywords: cloud, cryptography, Docker, Linux, security

Procedia PDF Downloads 198

Authors: Azza Taha Zaki

Abstract:

Technology-enhanced teaching has been in the limelight since the 90s when educators started investigating and experimenting with using computers in the classroom as a means of building 21^st. century skills and motivating students. The concept of technology-enhanced strategies in education is kaleidoscopic! It has meant different things to different educators. For the purpose of this paper, however, it will be used to refer to the diverse technology-based strategies used to support and enrich the flipped learning process, in the classroom and outside. The paper will investigate how technology is put in the service of teaching and learning to improve the students’ learning experience as manifested in students’ attendance and engagement, achievement rates and finally, students’ projects at the end of the semester. The results will be supported by a student survey about relevant specific aspects of their learning experience in the modules in the study.

Keywords: attendance, British University, Egypt, flipped, student achievement, student-centred, student engagement, students’ projects

Procedia PDF Downloads 118

Authors: Ellie Abdi

Abstract:

This paper is a review of a recently published book (April 2018) by Dr. Ellie Abdi. The book divides into two sections of 1) leadership in school organization and 2) pragmatic research in physical education professional development. The first part of the book explores school organizational development in terms of 1) communication development, 2) community development, and 3) decision making development. It concludes to acknowledge that decision making is the heart of educational management. This is while communication and community are essential to the development of the school organization. The role of a leader in a professional learning community (PLC) is acknowledged with the organizational development plan and moves onto 5 overall objectives of a professional development plan. It clarifies that professional learning community (PLC) benefits both students and professionals in education. Furthermore, professional development needs to be involved in opportunities to value diversity and foundations of learning, in addition to search for veteran teachers who offer a rich combination of experience and perspective. School educational platform in terms of teacher training in physical education is discussed in the second part. The book reviews that well-designed programs are powerful and constructive ways to identify the strength and weaknesses of teachers. Post-positivism, constructivism, advocacy/participatory, and pragmatism in teacher education are also disclosed. The book specifically unfolds pragmatic research in professional development of physical education. It provides researchers, doctoral, and masters level students with defined examples. In summary, the book shows how appropriate it is when many different traditions are displayed in a pragmatic way, following the stages of research from development to dissemination.

Keywords: leadership, physical education, pragmatic, professional development

Procedia PDF Downloads 162

Authors: Amritesh Srivastava, Gaurav Sharma

Abstract:

The purpose of this project is to develop an open source object storage system that is highly durable, scalable and reliable. There are two representative systems in cloud computing: Google and Amazon. Their storage systems for Google GFS and Amazon S3 provide high reliability, performance and stability. Our proposed system is highly inspired from Amazon S3. We are using Hadoop Distributed File System (HDFS) Java API to implement our system. We propose the architecture of object storage system based on Hadoop. We discuss the requirements of our system, what we expect from our system and what problems we may encounter. We also give detailed design proposal along with the abstract source code to implement it. The final goal of the system is to provide REST based access to our object storage system that exists on top of HDFS.

Keywords: Hadoop, HBase, object storage, REST

Procedia PDF Downloads 339

Authors: Khlif Hamadi

Abstract:

The principal aim of our research is to analyze the impact of the adoption of e-management approach on the performance of Tunisian firms. The method of structural equation was adopted to conduct our exploratory and confirmatory analysis. The results arising from the questionnaire sent to 155 E-managers affirm that the adoption of e-management approach influences the performance of Tunisian firms. The results of the questionnaire show that e-management favors the deployment of ICT usage and contributes enormously to the performance of the modern enterprise. The theoretical and practical implications of the study, as well as directions for future research, are discussed.

Keywords: e-management, ICT Deployment, organizational performance, e-manager

Procedia PDF Downloads 344