Search results for: machine learning tools and techniques

Authors: Vanessa Kummer, Maik Meusel

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Real estate demand estimates are typically derived from transaction data. However, in regions with excess demand, transactions are driven by supply and therefore do not indicate what people are actually looking for. To estimate the demand for housing in Switzerland, search subscriptions from all important Swiss real estate platforms are used. These data do, however, suffer from missing information—for example, many users do not specify how many rooms they would like or what price they would be willing to pay. In economic analyses, it is often the case that only complete data is used. Usually, however, the proportion of complete data is rather small which leads to most information being neglected. Also, the data might have a strong distortion if it is complete. In addition, the reason that data is missing might itself also contain information, which is however ignored with that approach. An interesting issue is, therefore, if for economic analyses such as the one at hand, there is an added value by using the whole data set with the imputed missing values compared to using the usually small percentage of complete data (baseline). Also, it is interesting to see how different algorithms affect that result. The imputation of the missing data is done using unsupervised learning. Out of the numerous unsupervised learning approaches, the most common ones, such as clustering, principal component analysis, or neural networks techniques are applied. By training the model iteratively on the imputed data and, thereby, including the information of all data into the model, the distortion of the first training set—the complete data—vanishes. In a next step, the performances of the algorithms are measured. This is done by randomly creating missing values in subsets of the data, estimating those values with the relevant algorithms and several parameter combinations, and comparing the estimates to the actual data. After having found the optimal parameter set for each algorithm, the missing values are being imputed. Using the resulting data sets, the next step is to estimate the willingness to pay for real estate. This is done by fitting price distributions for real estate properties with certain characteristics, such as the region or the number of rooms. Based on these distributions, survival functions are computed to obtain the functional relationship between characteristics and selling probabilities. Comparing the survival functions shows that estimates which are based on imputed data sets do not differ significantly from each other; however, the demand estimate that is derived from the baseline data does. This indicates that the baseline data set does not include all available information and is therefore not representative for the entire sample. Also, demand estimates derived from the whole data set are much more accurate than the baseline estimation. Thus, in order to obtain optimal results, it is important to make use of all available data, even though it involves additional procedures such as data imputation.

Keywords: demand estimate, missing-data imputation, real estate, unsupervised learning

Procedia PDF Downloads 280

Authors: Abiodun Ladanu Ajala, Wuyi Oke

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Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

Procedia PDF Downloads 585

Authors: V. Jagadeesh, K. Venkata Subbaiah, P. Govinda Rao

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This paper explaining about the significance of information technology tools and software packages in supply chain management (SCM) in order to manage the entire supply chain. Managing materials flow and financial flow and information flow effectively and efficiently with the aid of information technology tools and packages in order to deliver right quantity with right quality of goods at right time by using right methods and technology. Information technology plays a vital role in streamlining the sales forecasting and demand planning and Inventory control and transportation in supply networks and finally deals with production planning and scheduling. It achieves the objectives by streamlining the business process and integrates within the enterprise and its extended enterprise. SCM starts with customer and it involves sequence of activities from customer, retailer, distributor, manufacturer and supplier within the supply chain framework. It is the process of integrating demand planning and supply network planning and production planning and control. Forecasting indicates the direction for planning raw materials in order to meet the production planning requirements. Inventory control and transportation planning allocate the optimal or economic order quantity by utilizing shortest possible routes to deliver the goods to the customer. Production planning and control utilize the optimal resources mix in order to meet the capacity requirement planning. The above operations can be achieved by using appropriate information technology tools and software packages for the supply chain management.

Keywords: supply chain management, information technology, business process, extended enterprise

Procedia PDF Downloads 374

Authors: Behnam Madadnia

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For several years, 3D-shaped electronics have been rising, with many uses in home appliances, automotive, and manufacturing. One of the biggest challenges in the fabrication of 3D shape electronics, which are made by thermoforming, is repeatable and accurate component positioning, and typically there is no control over the final position of the component. This paper aims to address this issue and present a reliable approach for guiding the electronic components in the desired place during thermoforming. We have proposed a heat-control mask in the thermoforming machine to control the heating of the polymer, not allowing specific parts to be formable, which can assure the conductive traces' mechanical stability during thermoforming of the substrate. We have verified our approach's accuracy by applying our method on a real industrial semi-sphere mold for positioning 7 LEDs and one touch sensor. We measured the LEDs' position after thermoforming to prove the process's repeatability. The experiment results demonstrate that the proposed method is capable of positioning electronic components in thermoformed 3D electronics with high precision.

Keywords: 3D-shaped electronics, electronic components, thermoforming, component positioning

Procedia PDF Downloads 90

Authors: T. Keiller, E. Hindman, P. Hassmen, K. Radford, L. Lavrencic

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Background: Psychosocial disadvantage is associated with impaired cognitive abilities, with executive functioning (EF) abilities particularly vulnerable. EF abilities strongly predict general daily functioning, educational and career prospects, and health choices. A reliable and valid assessment of EF is important to support appropriate care and intervention strategies. However, evidence-based EF assessment tools for use with Aboriginal Australians are limited. Aim and Method: This research aims to develop and validate a culturally appropriate EF tool for use with indigenous Australians. To this end, Study One aims to review current literature examining the benefits and disadvantages of current EF assessment tools for use with Indigenous Australians. Study Two aims to collate expert opinion on the strengths and weaknesses of various current EF assessment tools for use with Indigenous Australians using Delphi methodology with experienced psychologists (n = 10). The initial two studies will inform the development of a culturally appropriate assessment tool. Study Three aims to evaluate the psychometric properties of the tool with an Indigenous sample living in the New South Wales Mid-North Coast. The study aims to quantify the predictive validity of this tool via comparison to functionality predictors and neuropsychological assessment scores. Study Four aims to collect qualitative data surrounding the feasibility and acceptability of the tool among indigenous Australians and health professionals. Expected Results: Findings from this research are likely to inform cognitive assessment practices and tool selection for health professionals conducting cognitive assessments with Indigenous Australians. Improved assessment of EF will inform appropriate care and intervention strategies for individuals with EF deficits.

Keywords: aboriginal Australians, assessment tool, cognition, executive functioning

Procedia PDF Downloads 267

Authors: Avi Shrivastava

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In 2021, two heart-wrenching scenes, shown live on television screens across countries, painted a grim picture of refugees. One of them was of people clinging onto an airplane's wings in their desperate attempt to flee war-torn Afghanistan. They ultimately fell to their death. The other scene was the U.S. government authorities separating children from their parents or guardians to deter migrants/refugees from coming to the U.S. These events show the desperation refugees feel when they are trying to leave their homes in disaster zones. However, data paints a grave picture of the current refugee situation. It also indicates that a bleak future lies ahead for the refugees across the globe. Data and information are the two threads that intertwine to weave the shimmery fabric of modern society. Data and information are often used interchangeably, but they differ considerably. For example, information analysis reveals rationale, and logic, while data analysis, on the other hand, reveals a pattern. Moreover, patterns revealed by data can enable us to create the necessary tools to combat huge problems on our hands. Data analysis paints a clear picture so that the decision-making process becomes simple. Geopolitical and economic data can be used to predict future refugee hotspots. Accurately predicting the next refugee hotspots will allow governments and relief agencies to prepare better for future refugee crises. The refugee crisis does not have binary answers. Given the emotionally wrenching nature of the ground realities, experts often shy away from realistically stating things as they are. This hesitancy can cost lives. When decisions are based solely on data, emotions can be removed from the decision-making process. Data also presents irrefutable evidence and tells whether there is a solution or not. Moreover, it also responds to a nonbinary crisis with a binary answer. Because of all that, it becomes easier to tackle a problem. Data science and A.I. can predict future refugee crises. With the recent explosion of data due to the rise of social media platforms, data and insight into data has solved many social and political problems. Data science can also help solve many issues refugees face while staying in refugee camps or adopted countries. This paper looks into various ways data science can help solve refugee problems. A.I.-based chatbots can help refugees seek legal help to find asylum in the country they want to settle in. These chatbots can help them find a marketplace where they can find help from the people willing to help. Data science and technology can also help solve refugees' many problems, including food, shelter, employment, security, and assimilation. The refugee problem seems to be one of the most challenging for social and political reasons. Data science and machine learning can help prevent the refugee crisis and solve or alleviate some of the problems that refugees face in their journey to a better life. With the explosion of data in the last decade, data science has made it possible to solve many geopolitical and social issues.

Keywords: refugee crisis, artificial intelligence, data science, refugee camps, Afghanistan, Ukraine

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Authors: Malini Ganapathy, Sarjit Kaur

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Maximising learning with higher-order thinking skills with Information and Communications Technology (ICT) has been deep-rooted and emphasised in various developed countries such as the United Kingdom, the United States of America and Singapore. The transformation of the education curriculum in the Malaysia Education Development Plan (PPPM) 2013-2025 focuses on the concept of Higher Order Thinking (HOT) skills which aim to produce knowledgeable students who are critical and creative in their thinking and can compete at the international level. HOT skills encourage students to apply, analyse, evaluate and think creatively in and outside the classroom. In this regard, the National Education Blueprint (2013-2025) is grounded based on high-performing systems which promote a transformation of the Malaysian education system in line with the vision of Malaysia’s National Philosophy in achieving educational outcomes which are of world class status. This study was designed to investigate ESL students’ learning practices on the emphasis of promoting HOTs while using ICT in their curricula. Data were collected using a stratified random sampling where 100 participants were selected to take part in the study. These respondents were a group of undergraduate students who undertook ESL courses in a public university in Malaysia. A three-part questionnaire consisting of demographic information, students’ learning experience and ICT utilization practices was administered in the data collection process. Findings from this study provide several important insights on students’ learning experiences and ICT utilization in developing HOT skills.

Keywords: English as a second language students, critical and creative thinking, learning, information and communication technology and higher order thinking skills

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Authors: Sara Corvino

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The aim of this study is to explore the potential of inclusive learning and assessment strategies to foster students' engagement with historical debates surrounding the field of graphic design. The goal is to respond to the diversity of L4 Graphic Design students, at Nottingham Trent University, in a way that instead of 'lowering standards' can benefit everyone. This research tests, measures, and evaluates the impact of a specific intervention, an assessment task, to develop students' critical visual analysis skills and stimulate a deeper engagement with the subject matter. Within the action research approach, this work has followed a case study research method to understand students' views and perceptions of a specific project. The primary methods of data collection have been: anonymous electronic questionnaire and a paper-based anonymous critical incident questionnaire. NTU College of Business Law and Social Sciences Research Ethics Committee granted the Ethical approval for this research in November 2019. Other methods used to evaluate the impact of this assessment task have been Evasys's report and students' performance. In line with the constructivist paradigm, this study embraces an interpretative and contextualized analysis of the collected data within the triangulation analytical framework. The evaluation of both qualitative and quantitative data demonstrates that active learning strategies and the disruption of thinking patterns can foster greater students' engagement and can lead to meaningful learning.

Keywords: active learning, assessment for learning, graphic design, higher education, student engagement

Procedia PDF Downloads 172

Authors: Jane E. Souyave, Judith Bower

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This study is an ongoing collaborative project between the University of Central Lancashire and the Alzheimer’s Society to design and test the idea of using interactive tools for a person living with dementia and their carers. It is hoped that the tools will fulfill the possible needs of engagement and interaction as dementia progresses, therefore enhancing wellbeing and improving quality of life for the person with dementia and their carers. The project was informed by Kitwood’s five psychological needs for producing wellbeing and explored evidence that fidgeting is often seen as a form of agitation and a negative symptom of dementia. Although therapy for agitation may be well established, there is a lack of appropriate items aimed at people in the later stage of dementia, that are not childlike or medical in their aesthetic. Individuals may fidget in a particular way and the tools in the Fidget Widget Toolkit have been designed to encourage repetitive movements of the hand, specifically to address the abilities of people with relatively advanced dementia. As an intervention, these tools provided a new approach that had not been tested in dementia care. Prototypes were created through an iterative design process and tested with a number of people with dementia and their carers, using quantitative and qualitative methods. Dementia Care Mapping was used to evaluate the impact of the intervention in group settings. Cohen Mansfield’s Agitation Inventory was used to record the daily use and interest of the intervention for people in their usual place of residence. The results informed the design of a new set of devices to promote safe, stigma free fidgeting as a positive experience, meaningful activity and enhance wellbeing for people in the later stage of dementia. The outcomes addressed the needs of individuals by reducing agitation and restlessness through helping them to connect, engage and act independently, providing the means of doing something for themselves that they were able to do. The next stage will be to explore the commercial feasibility of the Fidget Widget Toolkit so that it can be introduced as good practice and innovation in dementia care. It could be used by care homes, with carers and their families to support wellbeing and lead the way in providing some positive experiences and person-centred approaches that are lacking in the later stage of dementia.

Keywords: dementia, design, fidgeting, healthcare, positive moments, quality of life, wellbeing

Procedia PDF Downloads 269

Authors: Pitsanu Tongkhow, Pichet Jiraprasertwong

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This research investigates risk factors for defective products in autoparts factories. Under a Bayesian framework, a generalized linear mixed model (GLMM) in which the dependent variable, the number of defective products, has a Poisson distribution is adopted. Its performance is compared with the Poisson GLM under a Bayesian framework. The factors considered are production process, machines, and workers. The products coded RT50 are observed. The study found that the Poisson GLMM is more appropriate than the Poisson GLM. For the production Process factor, the highest risk of producing defective products is Process 1, for the Machine factor, the highest risk is Machine 5, and for the Worker factor, the highest risk is Worker 6.

Keywords: defective autoparts products, Bayesian framework, generalized linear mixed model (GLMM), risk factors

Procedia PDF Downloads 563

Authors: Deepak Singh, Rail Kuliev

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This research article explores the significance of advanced data visualization techniques in enhancing decision-making processes within the oil and gas exploration and production domain. With the oil and gas industry facing numerous challenges, effective interpretation and analysis of vast and diverse datasets are crucial for optimizing exploration strategies, production operations, and risk assessment. The article highlights the importance of data visualization in managing big data, aiding the decision-making process, and facilitating communication with stakeholders. Various advanced data visualization techniques, including 3D visualization, augmented reality (AR), virtual reality (VR), interactive dashboards, and geospatial visualization, are discussed in detail, showcasing their applications and benefits in the oil and gas sector. The article presents case studies demonstrating the successful use of these techniques in optimizing well placement, real-time operations monitoring, and virtual reality training. Additionally, the article addresses the challenges of data integration and scalability, emphasizing the need for future developments in AI-driven visualization. In conclusion, this research emphasizes the immense potential of advanced data visualization in revolutionizing decision-making processes, fostering data-driven strategies, and promoting sustainable growth and improved operational efficiency within the oil and gas exploration and production industry.

Keywords: augmented reality (AR), virtual reality (VR), interactive dashboards, real-time operations monitoring

Procedia PDF Downloads 79

Authors: M. Mueller, M. Kuehn, M. Voelker

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In small and medium-sized enterprises (SMEs), the challenge is to create a well-grounded and reliable basis for process analysis, optimization and planning due to a lack of data. SMEs have limited access to methods with which they can effectively and efficiently analyse processes and identify cause-and-effect relationships in order to generate the necessary database and derive optimization potential from it. The implementation of digitalization within the framework of Industry 4.0 thus becomes a particular necessity for SMEs. For these reasons, the abstract presents an analysis methodology that is subject to the objective of developing an SME-appropriate methodology for efficient, temporarily feasible data collection and evaluation in flexible production and logistics systems as a basis for process analysis and optimization. The overall methodology focuses on retrospective, event-based tracing and analysis of material flow objects. The technological basis consists of Bluetooth low energy (BLE)-based transmitters, so-called beacons, and smart mobile devices (SMD), e.g. smartphones as receivers, between which distance data can be measured and derived motion profiles. The distance is determined using the Received Signal Strength Indicator (RSSI), which is a measure of signal field strength between transmitter and receiver. The focus is the development of a software-based methodology for interpretation of relative movements of transmitters and receivers based on distance data. The main research is on selection and implementation of pattern recognition methods for automatic process recognition as well as methods for the visualization of relative distance data. Due to an existing categorization of the database regarding process types, classification methods (e.g. Support Vector Machine) from the field of supervised learning are used. The necessary data quality requires selection of suitable methods as well as filters for smoothing occurring signal variations of the RSSI, the integration of methods for determination of correction factors depending on possible signal interference sources (columns, pallets) as well as the configuration of the used technology. The parameter settings on which respective algorithms are based have a further significant influence on result quality of the classification methods, correction models and methods for visualizing the position profiles used. The accuracy of classification algorithms can be improved up to 30% by selected parameter variation; this has already been proven in studies. Similar potentials can be observed with parameter variation of methods and filters for signal smoothing. Thus, there is increased interest in obtaining detailed results on the influence of parameter and factor combinations on data quality in this area. The overall methodology is realized with a modular software architecture consisting of independently modules for data acquisition, data preparation and data storage. The demonstrator for initialization and data acquisition is available as mobile Java-based application. The data preparation, including methods for signal smoothing, are Python-based with the possibility to vary parameter settings and to store them in the database (SQLite). The evaluation is divided into two separate software modules with database connection: the achievement of an automated assignment of defined process classes to distance data using selected classification algorithms and the visualization as well as reporting in terms of a graphical user interface (GUI).

Keywords: event-based tracing, machine learning, process classification, parameter settings, RSSI, signal smoothing

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Authors: Biki Sarmah, Priyanko Raj Mudiar

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In the modern world of remotely interactive virtual reality-based learning and teaching, including professional skill-building training and acquisition practices, as well as data acquisition and robotic systems, the revolutionary application or implementation of field-programmable neurostimulator aids and first-hand interactive sensitisation techniques into 3D holographic audio-visual platforms have been a coveted dream of many scholars, professionals, scientists, and students. Integration of 'kinaesthetic vibrotactile haptic perception' along with an actuated step magnitude contact profiloscopy in augmented reality-based learning platforms and professional training can be implemented by using an extremely calculated and well-coordinated image telemetry including remote data mining and control technique. A real-time, computer-aided (PLC-SCADA) field calibration based algorithm must be designed for the purpose. But most importantly, in order to actually realise, as well as to 'interact' with some 3D holographic models displayed over a remote screen using remote laser image telemetry and control, all spatio-physical parameters like cardinal alignment, gyroscopic compensation, as well as surface profile and thermal compositions, must be implemented using zero-order type 1 actuators (or transducers) because they provide zero hystereses, zero backlashes, low deadtime as well as providing a linear, absolutely controllable, intrinsically observable and smooth performance with the least amount of error compensation while ensuring the best ergonomic comfort ever possible for the users.

Keywords: haptic feedback, kinaesthetic vibrotactile 3D design, medical simulation training, piezo diaphragm based actuator

Procedia PDF Downloads 160

Authors: Fu-Chi Chuang, Yu-Liang, Chang, Wen-Der Wang

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Our environment has been contaminated by many artificial chemicals, such as plastics, pesticides. Many of them have hormone-like activity and are classified as 'environmental hormone (also named endocrine disruptors)'. These chemicals interfere with or mimic hormones have adverse effects that persist into adulthood. Environmental education is an important way to teach students to become engaged in real-world issues that transcend classroom walls. Elementary education is the first stage to perform environmental education and it is an important component to help students develop adequate environmental knowledge, attitudes, and behavior. However, elementary teachers' knowledge plays a critical role in this mission. Therefore, we use a questionnaire to survey the knowledge of environmental hormone of elementary school teachers and their learning motivation of the environmental hormone-regarding knowledge. We collected 218 questionnaires from Taiwanese elementary teachers and the results indicate around 73% of elementary teachers do not have enough knowledge about environmental hormones. Our results also reveal the in-service elementary teachers’ learning motivation of environmental hormones knowledge is positively enhanced once they realized their insufficient cognitive ability of environmental hormones. We believe our study will provide the powerful reference for Ministry of Education to set up the policy of environmental education to enrich all citizens sufficient knowledge of the effects of the environmental hormone on organisms, and further to enhance our correct environmental behaviors.

Keywords: elementary teacher, environmental hormones, learning motivation, questionnaire

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Authors: Ilona Buchem, Carolin Gellner

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Over the last few years, the call for the support of senior learners in the development of their digital literacy has become prevalent, mainly due to the progression towards ageing societies paired with advances in digitalisation in all spheres of life, including e-health and electronic patient record (EPA). While major research efforts in supporting senior learners in developing digital literacy have been invested so far in e-learning focusing on knowledge acquisition and cognitive tasks, little research exists in learning models which target virtual mentoring and coaching with the help of pedagogical agents and address the social dimensions of learning. Research from studies with students in the context of formal education has already provided methods for designing intelligent virtual agents in support of personalised learning. However, this research has mostly focused on cognitive skills and has not yet been applied to the context of mentoring/coaching of senior learners, who have different characteristics and learn in different contexts. In this paper, we describe how insights from previous research can be used to develop an intelligent virtual learning coach (agent) for senior learners with a focus on building the social relationship between the agent and the learner and the key task of the agent to socialize learners to the larger context of digital literacy with a focus on electronic health records. Following current approaches to mentoring and coaching, the agent is designed not to enhance and monitor the cognitive performance of the learner but to serve as a trusted friend and advisor, whose role is to provide one-to-one guidance and support sharing of experiences among learners (peers). Based on literature review and synopsis of research on virtual agents and current coaching/mentoring models under consideration of the specific characteristics and requirements of senior learners, we describe the design framework which was applied to design an intelligent virtual learning coach as part of the e-learning system for digital literacy of senior learners in the ePA-Coach project founded by the German Ministry of Education and Research. This paper also presents the results from the evaluation study, which compared the use of the first prototype of the virtual learning coach designed according to the design framework with a voice narration in a multimedia learning environment with senior learners. The focus of the study was to validate the agent design in the context of the persona effect (Lester et al., 1997). Since the persona effect is related to the hypothesis that animated agents are perceived as more socially engaging, the study evaluated possible impacts of agent coaching in comparison with voice coaching on motivation, engagement, experience, and digital literacy.

Keywords: virtual learning coach, virtual mentor, pedagogical agent, senior learners, digital literacy, electronic health records

Procedia PDF Downloads 112

Authors: Reem AlKabbi, Hayat Ali, Mariam Yasser

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Nowadays, eGovernment websites are becoming indispensable for public, business, personal efficiency or even improvement of livelihoods. Using these websites, citizens undertake number of tasks that would otherwise be difficult or impossible. However, many of these websites are not accessible to all people' types including People with Disabilities (PWDs). Through Web Accessibility Guidelines, Web developers can develop Web applications that are accessible to PWDs. This research is to investigate the Accessibility of eGovernment websites in Kingdom of Bahrain. The accessibility was measured using Web Content Accessibility Guidelines (WCAG) and section 508. For the evaluation purpose, some automatic tools were used. Samples of 43 eGovernment websites were selected. The accessibility of the websites was analyzed by using several automatic evaluation tools such as Total Validator and Functional Accessibility Evaluator (FAE). The evaluation process revealed several errors according to the accessibility guidelines. This research provides few recommendations for further improvement of accessibility features of eGovernment websites based on the highlighted issues and key findings reported in this research.

Keywords: website accessibility, W3C, PWD, e-government

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Authors: Sachin Nagargoje

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Complete labeled data is often difficult to obtain in a practical scenario. Even if one manages to obtain the data, the quality of the data is always in question. In shopping vertical, offers are the input data, which is given by advertiser with or without a good quality of information. In this paper, an author investigated the possibility of using a very simple Semi-supervised learning approach to increase the recall of unhealthy offers (has badly written Offer Title or partial product details) in shopping vertical domain. The author found that the semisupervised learning method had improved the recall in the Smart Phone category by 30% on A=B testing on 10% traffic and increased the YoY (Year over Year) number of impressions per month by 33% at production. This also made a significant increase in Revenue, but that cannot be publicly disclosed.

Keywords: semi-supervised learning, clustering, recall, coverage

Procedia PDF Downloads 117

Authors: Eunice H. Li

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This e-poster explores some of the issues that are linked to Open Educational Resources (OER). It describes how OER is explained by experts in the field and relates its value in attaining and using knowledge. ‘Open', 'open pedagogy', self-direction, freedom, and autonomy are the main issues identified for the discussion. All of these issues make essential contributions to OER in one way or another. Nevertheless, there are seemingly areas of contentions with regard to applying these concepts in teaching and learning practices. For this e-Poster, it is the teaching-learning aspects of OER that it is primarily concerned with. The basis for the discussion comes from a 2013 critique of OER presented by Jeremy Knox of the University of Edinburgh, tutor of the MSc in Digital Education Programme. This discussion is also supported by the analysis of other research work and papers in this area. The general view on OER is that it is a useful tool for the advancement of learner-centred models of education, but in whatever context, pedagogy cannot be diminished and overlooked. It should take into consideration how to deal with the issues identified above in order to allow learners to gain full benefit from OER.

Keywords: open, pedagogy, e-learning technologies, autonomy, knowledge

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Authors: Eric Agrie Ambele

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The norms and models for learning pronunciation in relation to the teaching and learning of English pronunciation are key issues nowadays in English Language Teaching in ESL contexts. This paper discusses these issues based on a study on the attitudes of some Francophone university students in Cameroon towards three English accents spoken in Cameroon: Cameroon Francophone English (CamFE), Cameroon English (CamE), and Hyperlectal Cameroon English (near standard British English). With the desire to know more about the treatment that these English accents receive among these students, an aspect that had hitherto received little attention in the literature, a language attitude questionnaire, and the matched-guise technique was used to investigate this phenomenon. Two methods of data analysis were employed: (1) the percentage count procedure, and (2) the semantic differential scale. The findings reveal that the participants’ attitudes towards the selected accents vary in degree. Though Hyperlectal CamE emerged first, CamE second and CamFE third, no accent, on average, received a negative evaluation. It can be deduced from this findings that, first, CamE is gaining more and more recognition and can stand as an autonomous accent; second, that the participants all rated Hyperlectal CamE higher than CamE implies that they would be less motivated in a context where CamE is the learning model. By implication, in the teaching of English pronunciation to francophone learners learning English in Cameroon, Hyperlectal Cameroon English should be the model.

Keywords: teaching pronunciation, English accents, Francophone learners, attitudes

Procedia PDF Downloads 192

Authors: Daniel Asiamah Ameyaw

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This research attempts to investigate how lecturer evaluation makes a difference in enhancing higher education teaching and learning processes. The research questions to guide this research work states first as, “What are the perspectives on the difference made by evaluating academic teachers in order to enhance higher education teaching and learning processes?” and second, “What are the implications of the findings for Policy and Practice?” Data for this research was collected mainly through interviewing and partly documents review. Data analysis was conducted under the framework of grounded theory. The findings showed that for individual lecturer level, lecturer evaluation provides a continuous improvement of teaching strategies, and serves as source of data for research on teaching. At the individual student level, it enhances students learning process; serving as source of information for course selection by students; and by making students feel recognised in the educational process. At the institutional level, it noted that lecturer evaluation is useful in personnel and management decision making; it assures stakeholders of quality teaching and learning by setting up standards for lecturers; and it enables institutions to identify skill requirement and needs as a basis for organising workshops. Lecturer evaluation is useful at national level in terms of guaranteeing the competencies of graduates who then provide the needed manpower requirement of the nation. Besides, it mentioned that resource allocation to higher educational institution is based largely on quality of the programmes being run by the institution. The researcher concluded, that the findings have implications for policy and practice, therefore, higher education managers are expected to ensure that policy is implemented as planned by policy-makers so that the objectives can successfully be achieved.

Keywords: academic quality, higher education, lecturer evaluation, teaching and learning processes

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Authors: Azusa Katsumata

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Where there is collaboration between universities and companies in the educational context, companies seek ‘knowledge’ from universities and provide a ‘place of practice’ to them. Several universities have introduced activities aimed at the mutual enlightenment of a diversity of people in career education. However, several programs emphasize on delivering results, and on practicing the prepared materials as planned. Few programs focus on unexpected failures and setbacks. This way of learning is important in career education so that classmates can help each other, overcome difficulties, draw out each other’s strengths, and learn from them. Seijo University in Tokyo offered Tokyo Tourism, a Project-Based Learning course, as a first-year career education course until 2016. In cooperation with a travel agency, students participate in planning actual tourism products for foreigners visiting Japan, undertake tours serving as guides. This paper aims to study the 'learning platform' created by a series of processes such as the fieldwork, planning tours, the presentation, selling the tourism products, and guiding the tourists. We conducted a questionnaire to measure the development of work-related skills in class. From the results of the questionnaire, we can see, in the example of this class, that students demonstrated an increased desire to be pro-active and an improved motivation to learn. Students have not, however, acquired policy or business skills. This is appropriate for first-year careers education, but we need to consider how this can be incorporated into future courses. In the questionnaire filled out by the students after the class, the following results were found. Planning and implementing travel products while learning from each other, and helping the teams has led to improvements in the student workforce. This course is a collaborative project between Japanese universities and the 2020 Tokyo Olympics and Paralympic Games committee.

Keywords: university career education, platform of learning, project-based learning, collaboration between university and company

Procedia PDF Downloads 158

Authors: Ibtihal D. Mustafa, Mawia A. Hassan

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Tumor segmentation from MRI image is important part of medical images experts. This is particularly a challenging task because of the high assorting appearance of tumor tissue among different patients. MRI images are advance of medical imaging because it is give richer information about human soft tissue. There are different segmentation techniques to detect MRI brain tumor. In this paper, different procedure segmentation methods are used to segment brain tumors and compare the result of segmentations by using correlation and structural similarity index (SSIM) to analysis and see the best technique that could be applied to MRI image.

Keywords: MRI, segmentation, correlation, structural similarity

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Authors: Jaqueline Maria Ribeiro Vieira

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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). Previously we developed and proposed a novel strategy capable of detecting patterns at borehole images that may point to regions that have tension and breakout characteristics, based on segmented images. In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge data set configurations.

Keywords: image segmentation, oil well visualization, classifiers, data-mining, visual computer

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Authors: A. Djahbar, M. Aillerie, E. Bounadja

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In this paper we treat a new structure of a high-power actuator which is used to either industry or electric traction. Indeed, the actuator is constituted by two induction motors, the first is a six-phase motor connected in series with another three-phase motor via the stators. The whole is supplied by a single static converter. Our contribution in this paper is the optimization of the system supply source. This is feeding the multimotor group by a direct converter frequency without using the DC-link capacitor. The modelling of the components of multimotor system is presented first. Only the first component of stator currents is used to produce the torque/flux of the first machine in the group. The second component of stator currents is considered as additional degrees of freedom and which can be used for power conversion for the other connected motors. The decoupling of each motor from the group is obtained using the direct vector control scheme. Simulation results demonstrate the effectiveness of the proposed structure.

Keywords: induction machine, motor drives, scalar modulation technique, three-to-six phase matrix converter

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Authors: Susan Dodd

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This presentation details the methodology for teachers to identify and support a population of students who have historically been overlooked in regards to their educational needs. The twice exceptional (2e) student is a learner who is considered gifted and also has a learning disability, as defined by the Individuals with Disabilities Education Act (IDEA). Many of these students remain underserved throughout their educational careers because their exceptionalities may mask each other, resulting in a special population of students who are not achieving to their fullest potential. There are three common scenarios that may make the identification of a 2e student challenging. First, the student may have been identified as gifted, and her disability may go unnoticed. She could also be considered an under-achiever, or she may be able to compensate for her disability under the school works becomes more challenging. In the second scenario, the student may be identified as having a learning disability and is only receiving remedial services where his giftedness will not be highlighted. His overall IQ scores may be misleading because they were impacted by his learning disability. In the third scenario, the student is able to compensate for her ability well enough to maintain average scores, and she goes undetected as both gifted and learning disabled. Research in the area identifies the complexity involved in identifying 2e students, and how multiple forms of assessment are required. It is important for teachers to be aware of the common characteristics exhibited by many 2e students, so these learners can be identified and appropriately served. Once 2e students have been identified, teachers are then challenged to meet the varying needs of these exceptional learners. Strength-based teaching entails simultaneously providing gifted instruction as well as individualized accommodations for those students. Research in this field has yielded strategies that have proven helpful for teaching 2e students, as well as other students who may be struggling academically. Differentiated instruction, while necessary in all classrooms, is especially important for 2e students, as is encouragement for academic success. Teachers who take the time to really know their students will have a better understanding of each student’s strengths and areas for growth, and therefore tailor instruction to extend the intellectual capacities for optimal achievement. Teachers should also understand that some learning activities can prove very frustrating to students, and these activities can be modified based on individual student needs. Because 2e students can often become discouraged by their learning challenges, it is especially important for teachers to assist students in recognizing their own strengths and maintaining motivation for learning. Although research on the needs of 2e students has spanned across two decades, this population remains underserved in many educational institutions. Teacher awareness of the identification of and the support strategies for 2e students is critical for their success.

Keywords: gifted, learning disability, special needs, twice exceptional

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Authors: M. Rodionov, N. Sharapova, Z. Dedovets

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The article describes methods of preparation of future teachers that includes the entire diversity of traditional and computer-oriented methodological approaches. The authors reveal how, in the specific educational environment, a teacher can choose the most effective combination of educational technologies based on the nature of the learning task. The key conditions that determine such a choice are that the methodological approach corresponds to the specificity of the problem being solved and that it is also responsive to the individual characteristics of the students. The article refers to the training of students in the proper use of mathematical electronic tools for educational purposes. The preparation of future mathematics teachers should be a step-by-step process, building on specific examples. At the first stage, students optimally solve problems aided by electronic means of teaching. At the second stage, the main emphasis is on modeling lessons. At the third stage, students develop and implement strategies in the study of one of the topics within a school mathematics curriculum. The article also recommended the implementation of this strategy in preparation of future teachers and stated the possible benefits.

Keywords: education, methodological approaches, teacher, secondary school

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Authors: Prakash Singh

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Research studies affirm the view that gifted pupils are endowed with unique personality traits, enabling them to study at higher levels of thinking, at a faster pace, and with a greater degree of autonomy than their average counterparts. The focus of this study was whether high school gifted pupils are capable of studying an advanced level curriculum on their own by employing self-regulated learning (SRL) strategies. To be self-regulated, pupils are required to be metacognitively, motivationally, and behaviourally active participants in their own learning processes so that they are able to initiate and direct their personal curriculum efforts to acquire cognitive skills and knowledge, instead of being solely reliant on their teachers. Researchers working with gifted populations concede that limited studies have been conducted thus far to examine gifted pupils’ expertise in using SRL strategies to assume ownership of their learning. In order to conduct this investigation, an enriched module in Accounting for specifically gifted grade eleven pupils was developed, incorporating advanced level content, and use was made of the Post-test-Only Control Group Design to accomplish this research objective. The results emanating from this empirical study strongly suggest that SRL strategies can be employed to overcome a narrow, rigid approach that limits the education of gifted pupils in the regular classroom of the high school. SRL can meaningfully offer an alternative way to implement an advanced level curriculum for the gifted in the mainstream of education. This can be achieved despite the limitations of differentiation in the regular classroom.

Keywords: advanced level curriculum, high school gifted pupils, self-regulated learning, teachers’ professional competencies

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Authors: Adisorn Bansong, Walai Isarankura Na Ayudhaya, Aumporn Makanong

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A Development of an Instructional Model for Health Education was the aim to develop and study the effectiveness of an instructional model for health education to enhance self-regulation and learning achievement of lower secondary school students. It was the Quasi-Experimental Designs, used a Single-group Interrupted Time-series Designs, conducted by 2 phases: 1. To develop an instructional model based on Social Cognitive Theory and Strategic Life Planning. 2. To trial and evaluate effectiveness of an instructional model. The results as the following: i. An Instructional Model for Health Education consists of five main components: a) Attention b) Forethought c) Tactic Planning d) Execution and e) Reflection. ii. After an Instructional Model for Health Education has used for a semester trial, found the 4.07 percent of sample’s Self-Regulation higher and learning achievement on post-test were significantly higher than pre-test at .05 levels (p = .033, .000).

Keywords: social cognitive theory, strategic life planning, self-regulation, learning achievement

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Authors: S. Abera, T. Gidey, W. Terefe

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Introduction: Testing for HIV is the key entry point to HIV prevention, treatment, and care and support services. Hence, predictive data mining techniques can greatly benefit to analyze and discover new patterns from huge datasets like that of EDHS 2011 data. Objectives: The objective of this study is to build a predictive modeling for HIV testing and identify determinants of HIV testing for adults with age above fourteen years using data mining techniques. Methods: Cross-Industry Standard Process for Data Mining (CRISP-DM) was used to predict the model for HIV testing and explore association rules between HIV testing and the selected attributes among adult Ethiopians. Decision tree, Naïve-Bayes, logistic regression and artificial neural networks of data mining techniques were used to build the predictive models. Results: The target dataset contained 30,625 study participants; of which 16, 515 (53.9%) were women. Nearly two-fifth; 17,719 (58%), have never been tested for HIV while the rest 12,906 (42%) had been tested. Ethiopians with higher wealth index, higher educational level, belonging 20 to 29 years old, having no stigmatizing attitude towards HIV positive person, urban residents, having HIV related knowledge, information about family planning on mass media and knowing a place where to get testing for HIV showed an increased patterns with respect to HIV testing. Conclusion and Recommendation: Public health interventions should consider the identified determinants to promote people to get testing for HIV.

Keywords: data mining, HIV, testing, ethiopia

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Authors: Yee-May Chan

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In recent decades, it is observed that social work agencies have participated actively, and thus, have gradually been more influential in social work education in Hong Kong. The neo-liberal welfare ideologies and changing funding mode have transformed the landscape in social work practice and have also had a major influence on the fieldwork environment in Hong Kong. The aim of this research is to explore the educational role of social work agencies and examine in particular whether they are able to enhance or hinder critical reflective learning in fieldwork. In-depth interviews with 15 frontline social workers and managers in different social work agencies were conducted to collect their views and experience in helping social work students in fieldwork. The overall findings revealed that under the current social welfare context most social workers consider that the most important role of social work agencies in fieldwork is to help students prepare to fit-in the practice requirements and work within agencies’ boundary. The fit-for-purpose and down-to-earth view of fieldwork practice is seen as prevalent among most social workers. This narrow perception of agency’s role seems to be more favourable to competence-based approaches. In contrast, though critical reflection has been seen as important in addressing the changing needs of service users, the role of enhancing critical reflective learning has not been clearly expected or understood by most agency workers. The notion of critical reflection, if considered, has been narrowly perceived in fieldwork learning. The findings suggest that the importance of critical reflection is found to be subordinate to that of practice competence. The lack of critical reflection in the field is somehow embedded in the competence-based social work practice. In general, social work students’ critical reflection has not been adequately supported or enhanced in fieldwork agencies, nor critical reflective practice has been encouraged in fieldwork process. To address this situation, the role of social work agencies in fieldwork should be re-examined. To maximise critical reflective learning in the field, critical reflection as an avowed objective in fieldwork learning should be clearly stated. Concrete suggestions are made to help fieldwork agencies become more prepared to critical reflective learning. It is expected that the research can help social work communities to reflect upon the current realities of fieldwork context and to identify ways to strengthen agencies’ capacities to enhance critical reflective learning and practice of social work students.

Keywords: competence-based social work, critical reflective learning, fieldwork agencies, neo-liberal welfare

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