Search results for: technology enabled learning

Authors: Rodrigo Guimarães Santos

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The quality of public transport services has been considered as a critical factor by their users and also by users of individual transport. Thus, this dissertation aims to adapt a model that assesses the quality of public transport and determines its level of service based on the views of its users. The methodology is widely used by marketers and allows measuring the quality of services by assessing the perceptions and expectations of users. The adapted SERVQUAL was tested with users of public transport service users and car in Brasília-DF, city of Brazil. This research involved 241 questionnaires answered by people living in the various administrative regions of Brasília-DF. The analysis of the determinants pointed out that the quality of the public transport service offered in the city is low and users of public transport and cars have a high degree of expectations for improvement in all tested determinants. This method enabled the identification of the most critical determinants and those needing strategic actions for continuous improvement of quality. Adapting the SERVQUAL for a public transport service was satisfactory and demonstrated applicability to internal and external services, including measuring the public transport services in other cities with the opinion of the users.

Keywords: transportation services, quality services, servqual scale and marketing services

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Authors: Dilek Bilgiç

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Configuration Management (CM) is a discipline assuring the consistency between product information the reality all along the product lifecycle. Although the extensive benefits of this discipline, such as the direct impact on increasing return on investment, reducing lifecycle costs, are realized by most organizations. It is worth evaluating that CM functions might be successfully implemented in some organized anarchies. This paper investigates how to manage ambiguity in CM processes as an opportunity within an environment that has different types of complexities and choice arenas. It is not explained how to establish a configuration management organization in a company; more specifically, it is analyzed how to apply configuration management processes when different types of streams exist. From planning to audit, all the CM functions may provide different organization learning opportunities when those applied with the right leadership methods.

Keywords: configuration management, leadership, organizational analysis, organized anarchy, cm process, organizational learning, organizational maturity, configuration status accounting, leading innovation, change management

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Authors: Bruno Trstenjak, Dzenana Donko

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Data mining and classification of objects is the process of data analysis, using various machine learning techniques, which is used today in various fields of research. This paper presents a concept of hybrid classification model improved with the expert knowledge. The hybrid model in its algorithm has integrated several machine learning techniques (Information Gain, K-means, and Case-Based Reasoning) and the expert’s knowledge into one. The knowledge of experts is used to determine the importance of features. The paper presents the model algorithm and the results of the case study in which the emphasis was put on achieving the maximum classification accuracy without reducing the number of features.

Keywords: case based reasoning, classification, expert's knowledge, hybrid model

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Authors: James Ladzekpo

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Background: The urgent need to identify new pharmacological targets for diabetes treatment and prevention has been amplified by the disease's extensive impact on individuals and healthcare systems. A deeper insight into the biological underpinnings of diabetes is crucial for the creation of therapeutic strategies aimed at these biological processes. Current predictive models based on genetic variations fall short of accurately forecasting diabetes. Objectives: Our study aims to pinpoint key epigenetic factors that predispose individuals to diabetes. These factors will inform the development of an advanced predictive model that estimates diabetes risk from genetic profiles, utilizing state-of-the-art statistical and data mining methods. Methodology: We have implemented a recursive feature elimination with cross-validation using the support vector machine (SVM) approach for refined feature selection. Building on this, we developed six machine learning models, including logistic regression, k-Nearest Neighbors (k-NN), Naive Bayes, Random Forest, Gradient Boosting, and Multilayer Perceptron Neural Network, to evaluate their performance. Findings: The Gradient Boosting Classifier excelled, achieving a median recall of 92.17% and outstanding metrics such as area under the receiver operating characteristics curve (AUC) with a median of 68%, alongside median accuracy and precision scores of 76%. Through our machine learning analysis, we identified 31 genes significantly associated with diabetes traits, highlighting their potential as biomarkers and targets for diabetes management strategies. Conclusion: Particularly noteworthy were the Gradient Boosting Classifier and Multilayer Perceptron Neural Network, which demonstrated potential in diabetes outcome prediction. We recommend future investigations to incorporate larger cohorts and a wider array of predictive variables to enhance the models' predictive capabilities.

Keywords: diabetes, machine learning, prediction, biomarkers

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Authors: Samira Haghbin, Behnam Daryayelaal, Zeinab Amiri

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As a result of rapid progress of technology in various industries, the only way to survive in a competitive market of business is to update one's situation along with the said developments. During recent decades, Robotics and automation of the construction operation has emerged as one of the important technologies grabbing the attention of various industries and specially the construction industry. Because of the coming labor shortage of the aging society in the near future, robots will be used in construction fields more than ever. By predicting the condition of Robotics in world's future construction industry, we can make necessary preparations to face with needs imposed by the time and stay ahead. This article takes a library study approach and presents a literature review of existing studies with an aim to investigate the use of robotics in past, present and future of construction industry and make predictions on its' growth and change process. Therefore, to make familiar with this kind of technology and its' requirements in the construction industry, the status of Robotics in construction industry of different countries of the world has been studied and necessary context for its' future progress is expressed. It is hoped that identifying needs and required contexts will facilitate further development of advanced technologies such as robotics industry and lead to more preparation for future.

Keywords: future of robotics, construction industry, construction automation, trends of automation

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Authors: Mohammad Y. Abualhoul, Edgar Talavera Munoz, Fawzi Nashashibi

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The new emerging Visible Light Communication (VLC) technology has been subjected to intensive investigation, evaluation, and lately, deployed in the context of convoy-based applications for Intelligent Transportations Systems (ITS). The technology limitations were defined and supported by different solutions proposals to enhance the crucial alignment and mobility limitations. In this paper, we propose the incorporation of VLC technology and Lane-Centering (LC) technique to assure the VLC-connectivity by keeping the autonomous vehicle aligned to the lane center using vision-based lane detection in a convoy-based formation. Such combination can ensure the optical communication connectivity with a lateral error less than 30 cm. As soon as the road lanes are detectable, the evaluated system showed stable behavior independently from the inter-vehicle distances and without the need for any exchanged information of the remote vehicles. The evaluation of the proposed system is verified using VLC prototype and an empirical result of LC running application over 60 km in Madrid M40 highway.

Keywords: visible light communication, lane-centerin, platooning, intelligent transportation systems, road safety applications

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Authors: András Horkai, Attila Talamon, Viktória Sugár

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There is an urgent need nowadays to reduce energy demand and the current level of greenhouse gas emission and use renewable energy sources increase in energy efficiency. On the other hand, the European Union (EU) countries are largely dependent on energy imports and are vulnerable to disruption in energy supply, which may, in turn, threaten the functioning of their current economic structure. Residential buildings represent a significant part of the energy consumption of the building stock. Only a small part of the building stock is exchanged every year, thus it is essential to increase the energy efficiency of the existing buildings. Present paper focuses on the buildings built with industrialized technology only, and their opportunities in the boundaries of nearly zero-energy regulation. Current paper shows the emergence of panel construction method, and past and present of the ‘panel’ problem in Hungary with a short outlook to Europe. The study shows as well as the possibilities for meeting the nearly zero and cost optimized requirements for residential buildings by analyzing the renovation scenarios of an existing residential typology.

Keywords: Budapest, energy consumption, industrialized technology, nearly zero-energy buildings

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Authors: Paulo R. M. Andrade, Adriano B. Albuquerque, Otávio F. Frota, Robson V. Silveira, Fátima A. da Silva

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Information technology has been gaining more and more space whether in industry, commerce or even for personal use, but the misuse of it brings harm to the environment and human health as a result. Contribute to the sustainability of the planet is to compensate the environment, all or part of what withdraws it. The green computing also came to propose practical for use in IT in an environmentally correct way in aid of strategic management and communication. This work focuses on showing how a mobile application can help businesses reduce costs and reduced environmental impacts caused by its processes, through a case study of a public company in Brazil.

Keywords: green computing, information technology, e-government, sustainable development, mobile computing

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Authors: Sunico Armie Flores

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Early childhood education (ECE) is pivotal in shaping the future of individuals and society. This paper explores the collaborative efforts required among educators, families, and communities to create a collective impact on young children’s development. It delves into the importance of these partnerships, effective strategies for engagement, and the challenges and opportunities inherent in fostering such collaboration. By examining current research and practices, the paper aims to highlight the essential role of an integrated approach in achieving significant and sustainable improvements in early childhood outcomes.

Keywords: early childhood education, lifelong learning, cognitive development, socio-emotional development, educators, families, communities, collaborative efforts, collective impact, early learning environments, holistic development, high-quality ECE programs, investment in education

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Authors: Yiannis Vacanas, Kyriacos Themistocleous, Athos Agapiou, Diofantos Hadjimitsis

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Building Information Modelling (BIM) technology is considered by construction professionals as a very valuable process in modern design, procurement and project management. Construction professionals of all disciplines can use a single 3D model which BIM technology provides, to design a project accurately and furthermore monitor the progress of construction works effectively and efficiently. Unmanned Aerial Vehicles (UAVs), a technology initially developed for military applications, is now without any difficulty accessible and has already been used by commercial industries, including the construction industry. UAV technology has mainly been used for collection of images that allow visual monitoring of building and civil engineering projects conditions in various circumstances. UAVs, nevertheless, have undergone significant advances in equipment capabilities and now have the capacity to acquire high-resolution imagery from many angles in a cost effective manner, and by using photogrammetry methods, someone can determine characteristics such as distances, angles, areas, volumes and elevations of an area within overlapping images. In order to examine the potential of using a combination of BIM and UAV technologies in construction project management, this paper presents the results of a case study of a typical road construction project where the combined use of the two technologies was used in order to achieve efficient and accurate as-built data collection of the works progress, with outcomes such as volumes, and production of sections and 3D models, information necessary in project progress monitoring and efficient project management.

Keywords: BIM, project management, project monitoring, UAV

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Authors: Kedar J. Mahadeshwar

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Concept introduction: This paper talks about how an innovative cloud based analytics enabled solution that could address a major industry challenge that is approaching all of us globally faster than what one would think. The world of supply chain for drugs and devices is changing today at a rapid speed. In the US, the Drug Supply Chain Security Act (DSCSA) is a new law for Tracing, Verification and Serialization phasing in starting Jan 1, 2015 for manufacturers, repackagers, wholesalers and pharmacies / clinics. Similarly we are seeing pressures building up in Europe, China and many countries that would require an absolute traceability of every drug and device end to end. Companies (both manufacturers and distributors) can use this opportunity not only to be compliant but to differentiate themselves over competition. And moreover a country such as UAE can be the leader in coming up with a global solution that brings innovation in this industry. Problem definition and timing: The problem of counterfeit drug market, recognized by FDA, causes billions of dollars loss every year. Even in UAE, the concerns over prevalence of counterfeit drugs, which enter through ports such as Dubai remains a big concern, as per UAE pharma and healthcare report, Q1 2015. Distribution of drugs and devices involves multiple processes and systems that do not talk to each other. Consumer confidence is at risk due to this lack of traceability and any leading provider is at risk of losing its reputation. Globally there is an increasing pressure by government and regulatory bodies to trace serial numbers and lot numbers of every drug and medical devices throughout a supply chain. Though many of large corporations use some form of ERP (enterprise resource planning) software, it is far from having a capability to trace a lot and serial number beyond the enterprise and making this information easily available real time. Solution: The solution here talks about a service provider that allows all subscribers to take advantage of this service. The solution allows a service provider regardless of its physical location, to host this cloud based traceability and analytics solution of millions of distribution transactions that capture lots of each drug and device. The solution platform will capture a movement of every medical device and drug end to end from its manufacturer to a hospital or a doctor through a series of distributor or retail network. The platform also provides advanced analytics solution to do some intelligent reporting online. Why Dubai? Opportunity exists with huge investment done in Dubai healthcare city also with using technology and infrastructure to attract more FDI to provide such a service. UAE and countries similar will be facing this pressure from regulators globally in near future. But more interestingly, Dubai can attract such innovators/companies to run and host such a cloud based solution and become a hub of such traceability globally.

Keywords: cloud, pharmaceutical, supply chain, tracking

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Authors: Nosheen Fatima Warraich

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One of the most often used models in information system (IS) research is the technology acceptance model (TAM). This meta-analysis aims to measure the relationship between TAM variables, Perceived Ease of Use (PEOU), and Perceived Usefulness (PU) with users’ attitudes and behavioral intention (BI) in mobile and digital libraries context. It also examines the relationship of external variables (information quality and system quality) with TAM variables (PEOU and PU) in digital libraries settings. This meta-analysis was performed through PRISMA-P guidelines. Four databases (Google Scholar, Web of Science, Scopus, and LISTA) were utilized for searching, and the search was conducted according to defined criteria. The findings of this study revealed a large effect size of PU and PEOU with BI. There was also a large effect size of PU and PEOU with attitude. A medium effect size was found between SysQ -> PU, InfoQ-> PU, and SysQ -> PEOU. However, there was a small effect size between InfoQ and PEOU. It fills the literature gap and also confirms that TAM is a valid model for the acceptance and use of technology in mobile and digital libraries context. Thus, its findings would be helpful for developers and designers in designing and developing mobile library apps. It will also be beneficial for library authorities and system librarians in designing and developing digital libraries in academic settings.

Keywords: technology acceptance model (tam), perceived ease of use, perceived usefulness, information quality, system quality, meta-analysis, systematic review, digital libraries, and mobile library apps.

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Authors: Manikandakumar Shunmugavel, Ashwin Polishetty, Moshe Goldberg, Junior Nomani, Guy Littlefair

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Selective laser melting (SLM), a promising additive manufacturing (AM) technology, has a huge potential in the fabrication of Ti-6Al-4V near-net shape components. However, poor surface finish of the components fabricated from this technology requires secondary machining to achieve the desired accuracy and tolerance. Therefore, a systematic understanding of the machinability of SLM fabricated Ti-6Al-4V components is paramount to improve the productivity and product quality. Considering the significance of machining in SLM fabricated Ti-6Al-4V components, this research aim is to study the influence of build orientation on machinability characteristics by performing low speed orthogonal cutting tests. In addition, the machinability of SLM fabricated Ti-6Al-4V is compared with conventionally produced wrought Ti-6Al-4V to understand the influence of SLM technology on machining. This paper is an attempt to provide evidence to the hypothesis associated that build orientation influences cutting forces, chip formation and surface integrity during orthogonal cutting of SLM Ti-6Al-4V samples. Results obtained from the low speed orthogonal cutting tests highlight the practical importance of microstructure and build orientation on machinability of SLM Ti-6Al-4V.

Keywords: additive manufacturing, build orientation, machinability, titanium alloys (Ti-6Al-4V)

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Authors: Neha Ahirwar

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In the contemporary digital era, the rise of credit card fraud poses a significant threat to both financial institutions and consumers. As fraudulent activities become more sophisticated, there is an escalating demand for robust and effective fraud detection mechanisms. Advanced machine learning algorithms have become crucial tools in addressing this challenge. This paper conducts a thorough examination of the design and evaluation of a credit card fraud detection system, utilizing four prominent machine learning algorithms: random forest, logistic regression, decision tree, and XGBoost. The surge in digital transactions has opened avenues for fraudsters to exploit vulnerabilities within payment systems. Consequently, there is an urgent need for proactive and adaptable fraud detection systems. This study addresses this imperative by exploring the efficacy of machine learning algorithms in identifying fraudulent credit card transactions. The selection of random forest, logistic regression, decision tree, and XGBoost for scrutiny in this study is based on their documented effectiveness in diverse domains, particularly in credit card fraud detection. These algorithms are renowned for their capability to model intricate patterns and provide accurate predictions. Each algorithm is implemented and evaluated for its performance in a controlled environment, utilizing a diverse dataset comprising both genuine and fraudulent credit card transactions.

Keywords: efficient credit card fraud detection, random forest, logistic regression, XGBoost, decision tree

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Authors: Anum Rafiq

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Adolescence is a vulnerable period for youth across the world. It is a period of new learning with opportunities to understand and develop perspectives on health and well-being. With youth beginning to engage in intimate relationships at an earlier age in the 21st century, concentrating on the learning opportunity they have in school is paramount. The nature of what has been deemed important to teach in schools has changed throughout history, and the focus has shifted from home/family skills to teaching youth how to be competitive in the job market. Amidst this emphasis, opportunities for them exist to learn about building healthy intimate relationships, one of the foundational elements of most people’s lives. Using an Institutional Ethnography (IE), the lived experiences of youth in how they understand intimate relationships and how their learning experience is organized through the high school Health and Physical Education (H&PE) course is explored. An empirical inquiry into how the actual work of teachers and youth are socially organized by a biomedical, employment-related, and efficiency-based discourse is provided. Through thirty-two qualitative interviews with teachers and youth, a control of ruling relations such as institutional accountability circuits, performance reports, and timetabling over the experience of teachers and youth is found. One of the facets of the institutional accountability circuit is through the social organization of teaching and learning about healthy intimate relationships being framed through a biomedical discourse. In addition, the role of a hyper-focus on performance and evaluation is found as paramount in situating healthy intimacy discussions as inferior to neoliberally charged productivity measures such as employment skills. Lastly, due to the nature of institutional policies such as regulatory guidelines, teachers are largely influenced to avoid diving into discussions deemed risky or taboo by society, such as healthy intimacy in adolescence. The findings show how texts such as the H&PE curriculum, the Ontario College of Teachers (OCT) guidelines, Ministry of Education Performance Reports, and the timetable organize the day-to-day activities of teachers and students and reproduce different disjunctures for youth. This disjuncture includes some of their experiences being subordinated, difficulty relating to curriculum, and an experience of healthy living discussions being skimmed over across sites. The findings detail that the experience of youth in learning about healthy intimate relationships is not akin to the espoused vision outlined in policy documents such as the H&PE (2015) curriculum policy. These findings have implications for policymakers, activists, and school administration alike, which call for an investigation into who is in power when it comes to youth’s learning needs, as a pivotal period where youth can be equipped with life-changing knowledge is largely underutilized. A restructuring of existing institutional practices that allow for the social and institutional flexibility required to broach the topic of healthy intimacy in a comprehensive manner is required.

Keywords: health policy, intimate relationships, youth, education, ruling relations, sexual education, violence prevention

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Authors: Gayatri Mahajan

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Modern Construction Technology (CT) includes a broad range of advanced techniques and practices that bound the recent developments in material technology, design methods, quantity surveying, facility management, services, structural analysis and design, and other management education. Adoption of recent digital transformation technology is the need of today to speed up the business and is also the basis of construction improvement. Incorporating and practicing the technologies such as cloud-based communication and collaboration solution, Mobile Apps and 5G,3D printing, BIM and Digital Twins, CAD / CAM, AR/ VR, Big Data, IoT, Wearables, Blockchain, Modular Construction, Offsite Manifesting, Prefabrication, Robotic, Drones and GPS controlled equipment expedite the progress in the Construction industry (CI). Resources used are journaled research articles, web/net surfing, books, thesis, reports/surveys, magazines, etc. The outline of the research organization for this study is framed at four distinct levels in context to conceptualization, resources, innovative and emerging trends in CI, and better methods for completion of the construction projects. The present study conducted during 2020-2022 reveals that implementing these technologies improves the level of standards, planning, security, well-being, sustainability, and economics too. Application uses, benefits, impact, advantages/disadvantages, limitations and challenges, and policies are dealt with to provide information to architects and builders for smooth completion of the project. Results explain that construction technology trends vary from 4 to 15 for CI, and eventually, it reaches 27 for Civil Engineering (CE). The perspective of the most recent innovations, trends, tools, challenges, and solutions is highly embraced in the field of construction. The incorporation of the above said technologies in the pandemic Covid -19 and post-pandemic might lead to a focus on finding out effective ways to adopt new-age technologies for CI.

Keywords: BIM, drones, GPS, mobile apps, 5G, modular construction, robotics, 3D printing

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Authors: Safaa H. Sindi, Michael Roe

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This project divides supply chain (SC) models into seven Eras, according to the evolution of the market’s needs throughout time. The five earliest Eras describe the emergence of supply chains, while the last two Eras are to be created. Research objectives: The aim is to generate the two latest Eras with their respective models that focus on the consumable goods. Era Six contains the Optimal Multidimensional Matrix (OMM) that incorporates most characteristics of the SC and allocates them into four quarters (Agile, Lean, Leagile, and Basic SC). This will help companies, especially (SMEs) plan their optimal SC route. Era Seven creates an Automated Multidimensional Model (AMM) which upgrades the matrix of Era six, as it accounts for all the supply chain factors (i.e. Offshoring, sourcing, risk) into an interactive system with Heuristic Learning that helps larger companies and industries to select the best SC model for their market. Methodologies: The data collection is based on a Fuzzy-Delphi study that analyses statements using Fuzzy Logic. The first round of Delphi study will contain statements (fuzzy rules) about the matrix of Era six. The second round of Delphi contains the feedback given from the first round and so on. Preliminary findings: both models are applicable, Matrix of Era six reduces the complexity of choosing the best SC model for SMEs by helping them identify the best strategy of Basic SC, Lean, Agile and Leagile SC; that’s tailored to their needs. The interactive heuristic learning in the AMM of Era seven will help mitigate error and aid large companies to identify and re-strategize the best SC model and distribution system for their market and commodity, hence increasing efficiency. Potential contributions to the literature: The problematic issue facing many companies is to decide which SC model or strategy to incorporate, due to the many models and definitions developed over the years. This research simplifies this by putting most definition in a template and most models in the Matrix of era six. This research is original as the division of SC into Eras, the Matrix of Era six (OMM) with Fuzzy-Delphi and Heuristic Learning in the AMM of Era seven provides a synergy of tools that were not combined before in the area of SC. Additionally the OMM of Era six is unique as it combines most characteristics of the SC, which is an original concept in itself.

Keywords: Leagile, automation, heuristic learning, supply chain models

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Authors: Ghada A. Alfattni

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Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour

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Authors: Mohamed Bin Alhaj, Hexu Liu, Mohammed Sulaiman, Osama Abudayyeh

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An effective facility maintenance management (FMM) system plays a crucial role in improving the quality of services and maintaining the facility in good condition. Current FMM heavily relies on the quality of the data collection function of the FMM systems, at times resulting in inefficient FMM decision-making. The new technology-based crowdsourcing provides great potential to improve the current FMM practices, especially in terms of timeliness and quality of data. This research aims to investigate the feasibility of using new technology-driven crowdsourcing for FMM and highlight its opportunities and challenges. A survey was carried out to understand the human, data, system, geospatial, and automation characteristics of crowdsourcing for an educational campus FMM via social networks. The survey results were analyzed to reveal the challenges and recommendations for the implementation of crowdsourcing for FMM. This research contributes to the body of knowledge by synthesizing the challenges and opportunities of using crowdsourcing for facility maintenance and providing a road map for applying crowdsourcing technology in FMM. In future work, a conceptual framework will be proposed to support data-driven FMM using social networks.

Keywords: crowdsourcing, facility maintenance management, social networks

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Authors: Susan Cardillo

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This research will consider ways to bridge the gap between Computer Science and Media Communications and while doing so create Social Entrepreneurship for student success. New Media, as it has been referred to, is considered content available on-demand through Internet, a digital device, usually containing some kind of interactivity and creative participation. It is the interplay between technology, images, media and communications. The next generation of the newspaper, radio, television, and film students need to have a working knowledge of the technologies that are available for the creation of their work and taught to use this knowledge to create a voice. The work is interdisciplinary; in communications, we understand the necessity of reporting and disseminating information. In documentary film we understand the instructional and historic aspects of media and technology and in the non-profit sector, we see the need for expanding outlets for good. So, the true necessity is to utilize ‘new media’ technologies to advance social causes while reporting information, teaching and creating art. Goals: The goal of this research is to give communications students a better understanding of the technology that is both, currently at their disposal, and on the horizon, so that they can use it in their media, communications and art endeavors to be a voice for their generation. There is no longer a need to be a computer scientist to have a working knowledge of communication technologies and how they will benefit our work. There are many free and easy to use applications available for the creation of interactive communications. Methodology: This is Qualitative-Case Study that puts these ideas into action. There is a survey at the end of the experiment that is qualitative in nature and allows for the participants to share ideas and feelings about the technology and approach.

Keywords: interactive storytelling, web documentary, mass communications, teaching

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Authors: Minjuan Sun

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Ever since the late 1990s, China has experienced explosive growth in consumer lending, especially in short-term consumer loans, among which, the growth rate of non-bank lending has surpassed bank lending due to the development in financial technology. On the other hand, China does not have a universal credit scoring and registration system that can guide lenders during the processes of credit evaluation and risk control, for example, an individual’s bank credit records are not available for online lenders to see and vice versa. Given this context, the purpose of this paper is three-fold. First, we explore if and how alternative digital footprint data can be utilized to assess borrower’s creditworthiness. Then, we perform a comparative analysis of machine learning methods for the canonical problem of credit default prediction. Finally, we analyze, from an institutional point of view, the necessity of establishing a viable and nationally universal credit registration and scoring system utilizing online digital footprints, so that more people in China can have better access to the consumption loan market. Two different types of digital footprint data are utilized to match with bank’s loan default records. Each separately captures distinct dimensions of a person’s characteristics, such as his shopping patterns and certain aspects of his personality or inferred demographics revealed by social media features like profile image and nickname. We find both datasets can generate either acceptable or excellent prediction results, and different types of data tend to complement each other to get better performances. Typically, the traditional types of data banks normally use like income, occupation, and credit history, update over longer cycles, hence they can’t reflect more immediate changes, like the financial status changes caused by the business crisis; whereas digital footprints can update daily, weekly, or monthly, thus capable of providing a more comprehensive profile of the borrower’s credit capabilities and risks. From the empirical and quantitative examination, we believe digital footprints can become an alternative information source for creditworthiness assessment, because of their near-universal data coverage, and because they can by and large resolve the "thin-file" issue, due to the fact that digital footprints come in much larger volume and higher frequency.

Keywords: credit score, digital footprint, Fintech, machine learning

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Authors: Martin K. Steiger, Lukas Heisler, Hans-Georg Brachtendorf

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Deep neural networks and their variants form the backbone of many AI applications. Based on the so-called residual networks, a continuous formulation of such models as ordinary differential equations (ODEs) has proven advantageous since different techniques may be applied that significantly increase the learning speed and enable controlled trade-offs with the resulting error at the same time. For the evaluation of such models, high-performance numerical differential equation solvers are used, which also provide the gradients required for training. However, whether classical gradient-based methods are even applicable or which one yields the best results has not been discussed yet. This paper aims to redeem this situation by providing empirical results for different applications.

Keywords: deep neural networks, gradient-based learning, image processing, ordinary differential equation networks

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Authors: Shavindrie Cooray

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It is vital that students are supported in having balanced conversations about topics that might be controversial. This process is crucial to the development of critical thinking skills. This can be difficult to attain in e-learning environments, with some research finding students report a perceived loss in the quality of knowledge exchange and performance. This research investigated if Systems Theory could be applied to structure the discussion, improve information sharing, and reduce conflicts when students are working in online environments. This research involved 160 participants across four categories of student groups at a college in the Northeastern US. Each group was provided with a shared problem, and each group was expected to make a proposal for a solution. Two groups worked face-to-face; the first face to face group engaged with the problem and each other with no intervention from a facilitator; a second face to face group worked on the problem using Systems tools to facilitate problem structuring, group discussion, and decision-making. There were two types of virtual teams. The first virtual group also used Systems tools to facilitate problem structuring and group discussion. However, all interactions were conducted in a synchronous virtual environment. The second type of virtual team also met in real time but worked with no intervention. Findings from the study demonstrated that the teams (both virtual and face-to-face) using Systems tools shared more information with each other than the other teams; additionally, these teams reported an increased level of disagreement amongst their members, but also expressed more confidence and satisfaction with the experience and resulting decision compared to the other groups.

Keywords: e-learning, virtual teams, systems approach, conflicts

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Authors: L. Nevrivova, K. Lang, M. Kotoucek, D. Vsiansky

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This entry concerned with dense silica microstructure was produced as a part of a project within the Technology Agency of the Czech Republic which is being implemented in cooperation of the biggest producer of refractories the P-D Refractories CZ company with the research organisation Brno University of Technology. The paper is focused on the influence of mixture homogenisation and the influence of grain size of the mineraliser on the resulting utility properties of the material as well as its microstructure. It has a decisive influence on the durability of the material in a building structure. This paper is a continuation of a previously published study dealing with the suitability of various types of mineralising agents in terms of density, strength and mineral composition of silica. The entry describes the influence of the method of mixture homogenisation and the influence of granulometry of the applied Fe-mineralising agent on the resulting silica microstructure. Porosity, density, phase composition and microstructure of the experimentally prepared silica samples were examined and the results were discussed in context with the technology of homogenisation and firing temperature used. The properties of silica brick samples were compared to the sample without any Fe-mineraliser.

Keywords: silica bricks, Fe-mineraliser, mineralogical composition, new developed silica material

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Authors: Sakine Sincer

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In today’s world, the borders between countries and globalization are getting faster. It is an undeniable fact that this trend mostly results from the developments and improvements in technology. Technology, which dominates our lives to a great extent, has turned out to be one of the most important resources to be used in building an effective and fruitful educational atmosphere. Nowadays, technology is a significant means of arranging educational activities at all levels of education such as primary, secondary or tertiary education. This study aims at analyzing the attitudes of prep-class students towards computer-based foreign language education. Within the scope of this study, prep-class students at a university in Ankara, Turkey in 2013-2014 Academic Year participated in this study. The participants were asked to fill in 'Computer-Based Educational Attitude Scale.' The data gathered in this study were analyzed by means of using statistical devices such as means, standard deviation, percentage as well as t-test and ANOVA. At the end of the analysis, it was found out that the participants had a highly positive attitude towards computer-based language education.

Keywords: computer-based education, foreign language education, higher education, prep-class

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Authors: Chuanbo Xu, Xinying Li, Gejirifu De, Yunna Wu

Abstract:

Energy Internet (EI) is a new form that deeply integrates the Internet and the entire energy process from production to consumption. The assessment of energy efficient performance is of vital importance for the long-term sustainable development of EI project. Although the newly proposed fuzzy integrated cloud evaluation algorithm considers the randomness of uncertainty, it relies too much on the experience and knowledge of experts. Fortunately, the enrichment of EI data has enabled the utilization of data-driven methods. Therefore, the main purpose of this work is to assess the energy efficient of park-level EI by using a combination of a data-driven method with the fuzzy integrated cloud evaluation algorithm. Firstly, the indicators for the energy efficient are identified through literature review. Secondly, the artificial neural network (ANN)-based data-driven method is employed to cluster the values of indicators. Thirdly, the energy efficient of EI project is calculated through the fuzzy integrated cloud evaluation algorithm. Finally, the applicability of the proposed method is demonstrated by a case study.

Keywords: energy efficient, energy internet, data-driven, fuzzy integrated evaluation, cloud model

Procedia PDF Downloads 185

Authors: Li Jiuen Ong, Magdalin Cheong, Sri Rahayu, Lek Alexander, Pei Ting Tan

Abstract:

Background: Previous programme evaluations from the diabetes training programme conducted in Changi General Hospital revealed that healthcare professionals (HCPs) are keen to receive advance diabetes training and education, specifically in medical, nutritional therapy. HCPs also expressed a preference for interactive activities over didactic teaching methods to enhance their learning. Since the War on Diabetes was initiated by MOH in 2016, HCPs are challenged to be actively involved in continuous education to be better equipped to reduce the growing burden of diabetes. Hence, streamlining training to incorporate an element of fun is of utmost importance. Aim: The nutrition programme incorporates game play using an interactive board game that aims to provide a more conducive and less stressful environment for learning. The board game could be adapted for training of community HCPs, health ambassadors or caregivers to cope with the increasing demand of diabetes care in the hospital and community setting. Methodology: Stages for game’s conception (Jaffe, 2001) were adopted in the development of the interactive board game ‘Sweet Score™ ’ Nutrition concepts and topics in diabetes self-management are embedded into the game elements of varying levels of difficulty (‘Easy,’ ‘Medium,’ ‘Hard’) including activities such as a) Drawing/ sculpting (Pictionary-like) b)Facts/ Knowledge (MCQs/ True or False) Word definition) c) Performing/ Charades To study the effects of game play on knowledge acquisition and perceived experiences, participants were randomised into two groups, i.e., lecture group (control) and game group (intervention), to test the difference. Results: Participants in both groups (control group, n= 14; intervention group, n= 13) attempted a pre and post workshop quiz to assess the effectiveness of knowledge acquisition. The scores were analysed using paired T-test. There was an improvement of quiz scores after attending the game play (mean difference: 4.3, SD: 2.0, P<0.001) and the lecture (mean difference: 3.4, SD: 2.1, P<0.001). However, there was no significance difference in the improvement of quiz scores between gameplay and lecture (mean difference: 0.9, 95%CI: -0.8 to 2.5, P=0.280). This suggests that gameplay may be as effective as a lecture in terms of knowledge transfer. All the13 HCPs who participated in the game rated 4 out of 5 on the likert scale for the favourable learning experience and relevance of learning to their job, whereas only 8 out of 14 HCPs in the lecture reported a high rating in both aspects. 16. Conclusion: There is no known board game currently designed for diabetes training for HCPs.Evaluative data from future training can provide insights and direction to improve the game format and cover other aspects of diabetes management such as self-care, exercise, medications and insulin management. Further testing of the board game to ensure learning objectives are met is important and can assist in the development of awell-designed digital game as an alternative training approach during the COVID-19 pandemic. Learning through gameplay increases opportunities for HCPs to bond, interact and learn through games in a relaxed social setting and potentially brings more joy to the workplace.

Keywords: active learning, game, diabetes, nutrition

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Authors: Waqas Ahmed Khan Afridi, Subhas Chandra Mukhopadhyay, Bandita Mainali

Abstract:

The research paper presents a unique approach to evapotranspiration (ET) prediction using a Support Vector Machine (SVM) learning algorithm. The study leverages real-time sensor node data to develop an accurate and adaptable prediction model, addressing the inherent challenges of traditional ET estimation methods. The integration of the SVM algorithm with real-time sensor node data offers great potential to improve spatial and temporal resolution in ET predictions. In the model development, key input features are measured and computed using mathematical equations such as Penman-Monteith (FAO56) and soil water balance (SWB), which include soil-environmental parameters such as; solar radiation (Rs), air temperature (T), atmospheric pressure (P), relative humidity (RH), wind speed (u2), rain (R), deep percolation (DP), soil temperature (ST), and change in soil moisture (∆SM). The one-year field data are split into combinations of three proportions i.e. train, test, and validation sets. While kernel functions with tuning hyperparameters have been used to train and improve the accuracy of the prediction model with multiple iterations. This paper also outlines the existing methods and the machine learning techniques to determine Evapotranspiration, data collection and preprocessing, model construction, and evaluation metrics, highlighting the significance of SVM in advancing the field of ET prediction. The results demonstrate the robustness and high predictability of the developed model on the basis of performance evaluation metrics (R2, RMSE, MAE). The effectiveness of the proposed model in capturing complex relationships within soil and environmental parameters provide insights into its potential applications for water resource management and hydrological ecosystem.

Keywords: evapotranspiration, FAO56, KNIME, machine learning, RStudio, SVM, sensors

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Authors: Radek Novotný, Martina Maněnová

Abstract:

This article presents a summary of reviews on gender differences in perception of information and communication technology (ICT) by pupils in primary education. The article outlines the meaning of ICT in primary education then summarizes different studies of the use of ICT in primary education from the point of view of gender. The article also presents the specific differences of gender in the knowledge of modalities of use of specialized digital tools and the perception and value assigned to ICT, accordingly the article provides insight into the background of gender differences in performance in relation to ICT to determinate the complex meaning of pupils attitudes to the ICT.

Keywords: ICT in primary education, attitudes to ICT, gender differences, gender and ICT

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Authors: Olaniyi O. Omoyajowo

Abstract:

To be successful in today’s competitive global environment, manufacturing industry must be able to respond quickly to changes in technology. These changes in technology introduce new risks and hazards. The management of risk/hazard in a manufacturing process recommends method through which the success rate of an organization can be increased. Thus, there is a continual need for manufacturing industries to invest significant amount of resources in risk management, which in turn optimizes the production output and profitability of any manufacturing industry (if implemented properly). To help improve the existing risk prevention and mitigation practices in Small and Medium Enterprise (SME) in Nigeria Manufacturing Industries (NMI), the researcher embarks on this research to develop a systematic Risk Management process.

Keywords: manufacturing management, risk, risk management, SMEs

Procedia PDF Downloads 384