Search results for: digital learning environment

Authors: Pouya Vakili

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Since computers were first introduced into educational facilities, foreign language educators have been faced with the problem of integrating high-tech multimedia techniques into a traditional text-based curriculum. As studies of language teaching have pointed out, ‘Language teaching tends in practice to be eclectic…. There are not only exceptionally many paths and educational means for arriving at a given educational goal, but there are also many types of educational materials which can be used to achieve that goal’. For language educators who are trying to incorporate technology into their curricula, the choices seem endless. Yet the quantity, as well as the limitations, of available computer programs does not guarantee that these programs can be successfully integrated into a curriculum.

Keywords: curriculum, language teaching, learning, multimedia, technology

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Authors: Susanna Graziano, Lydia Krstic Ward

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The purpose of this presentation is to demonstrate the steps of using multimedia and collaborative platforms in project-based learning. The presentation will demonstrate the stages of the learning project with various components of independent and collaborative learning, where students research the topic, share information, prepare a survey, use social media (Facebook, Instagram, WhasApp) and collaborative platforms (wikispaces.com and Google docs) to collect, analyze and process data, then produce reports and logos to be displayed as a final product. At the beginning of the presentation participants will answer a questionnaire about project based learning and share their experience on using social media, real–world project work and collaborative learning. Using a PPP, the presentation will walk participants through the steps of a completed project where tertiary education students are involved in putting together a multimedia campaign for safe driving in Kuwait. The research component of the project entails taking a holistic view on the problem of the high death rate in traffic accidents. The final goal of the project is to lead students to raise public awareness about the importance of safe driving. The project steps involve using the social media and collaborative platforms for collecting data and sharing the required materials to be used in the final product – a display of written reports, slogans and videos, as well as oral presentations. The same structure can be used to organize a multimedia campaign focusing on other issues, whilst scaffolding on students’ ability to brainstorm, retrieve information, organize it and engage in collaborative/ cooperative learning whilst being immersed in content-based learning as well as in authentic tasks. More specifically, the project we carried out at Box Hill College was a real-world one and involved a multimedia Campaign for Safe Driving since reckless driving is one of the major problems in the country. The idea for the whole project started by a presentation given by a board member of the Kuwaiti Society for Traffic Safety who was invited to college and spoke about: • Driving laws in the country, • What causes car accidents, • Driving safety tips. The principal goal of this project was to let students consider problems of traffic in Kuwait from different points of view. They also had to address the number and causes of accidents, evaluate the effectiveness of the local traffic law in order to send a warning about the importance of safe driving and, finally, suggest ways of its improvement. Benefits included: • Engagement, • Autonomy, • Motivation, • Content knowledge, • Language mastery, • Enhanced critical thinking, • Increased metacognitive awareness, • Improved social skills, • Authentic experience.

Keywords: social media, online learning platforms, collaborative platforms, project based learning

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Authors: Bethany Wood

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The world pandemic led to a change in the way social media was used by audiences, with young people spending more hours on the platform due to lockdown. Reports by Ofcom have demonstrated that the internet is the second most popular platform for accessing news after television in the UK with social media and the internet ranked as the most popular platform to access news for those aged between 16-24. These statistics are unsurprising considering that at the time of writing, 98 percent of Generation Z (Gen Z) owned a smartphone and the subsequent ease and accessibility of social media. Technology is constantly developing and with this, its importance is becoming more prevalent with each generation: the Baby Boomers (1946-1964) consider it something useful whereas millennials (1981-1997) believe it a necessity for day to day living. Gen Z, otherwise known as the digital native, have grown up with this technology at their fingertips and social media is a norm. It helps form their identity, their affiliations and opens gateways for them to engage with news in a new way. It is a common misconception that Gen Z do not consume news, they are simply doing so in a different way to their predecessors. Using a sample of 800 18-20 year olds whilst utilising Generational theory, Actor Network Theory and the Social Shaping of Technology, this research provides a critical analyse regarding how Gen Z’s news consumption and engagement habits are developing along with technology to sculpture the future format of news and its distribution. From that perspective, allied with the empirical approach, it is possible to provide research orientated advice for the industry and even help to redefine traditional concepts of journalism.

Keywords: journalism, generation z, digital, social media

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Authors: Jean Marie Tshimula, Atsushi Togashi

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We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: Joan Esper Kuhnly, Jess Holden, Lynn Shelley, Nicole Kuhnly

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Empathy serves as a foundational nursing principle inherent in the nurse’s ability to form those relationships from which to care for patients. Evidence supports, including empathy in nursing and healthcare education, but there is limited data on what methods are effective to do so. Building evidence supports experiential and interactive learning methods to be effective for students to gain insight and perspective from a personalized experience. The purpose of this project is to evaluate learning activities designed to promote the attainment of empathic behaviors across 5 levels of the nursing curriculum. Quantitative analysis will be conducted on data from pre and post-learning activities using the Toronto Empathy Questionnaire. The main hypothesis, that simulation learning activities will increase empathy, will be examined using a repeated measures Analysis of Variance (ANOVA) on Pre and Post Toronto Empathy Questionnaire scores for three simulation activities (Stroke, Poverty, Dementia). Pearson product-moment correlations will be conducted to examine the relationships between continuous demographic variables, such as age, credits earned, and years practicing, with the dependent variable of interest, Post Test Toronto Empathy Scores. Krippendorff’s method of content analysis will be conducted to identify the quantitative incidence of empathic responses. The researchers will use Colaizzi’s descriptive phenomenological method to describe the students’ simulation experience and understand its impact on caring and empathy behaviors employing bracketing to maintain objectivity. The results will be presented, answering multiple research questions. The discussion will be relevant to results and educational pedagogy in the nursing curriculum as they relate to the attainment of empathic behaviors.

Keywords: curriculum, empathy, nursing, simulation

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Authors: John Zanetich

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Designing an educational activity that encourages inquiry and collaboration is key to engaging students in meaningful learning. Educational Information and Communications Technology (EICT) plays an important role in facilitating cooperative and collaborative learning in the classroom. The EICT also facilitates students’ learning and development of the critical thinking skills needed to solve real world problems. Projects and activities based on constructivism encourage students to embrace complexity as well as find relevance and joy in their learning. It also enhances the students’ capacity for creative and responsible real-world problem solving. Classroom activities based on constructivism offer students an opportunity to develop the higher–order-thinking skills of defining problems and identifying solutions. Participating in a classroom project is an activity for both acquiring experiential knowledge and applying new knowledge to practical situations. It also provides an opportunity for students to integrate new knowledge into a skill set using reflection. Classroom projects can be developed around a variety of learning objects including social media, knowledge management and learning communities. The construction of meaning through project-based learning is an approach that encourages interaction and problem-solving activities. Projects require active participation, collaboration and interaction to reach the agreed upon outcomes. Projects also serve to externalize the invisible cognitive and social processes taking place in the activity itself and in the student experience. This paper describes a classroom project designed to elicit interactions by helping students to unfreeze existing knowledge, to create new learning experiences, and then refreeze the new knowledge. Since constructivists believe that students construct their own meaning through active engagement and participation as well as interactions with others. knowledge management can be used to guide the exchange of both tacit and explicit knowledge in interpersonal interactions between students and guide the construction of meaning. This paper uses an action research approach to the development of a classroom project and describes the use of technology, social media and the active use of tacit knowledge in the college classroom. In this project, a closed group Facebook page becomes the virtual classroom where interaction is captured and measured using engagement analytics. In the virtual learning community, the principles of knowledge management are used to identify the process and components of the infrastructure of the learning process. The project identifies class member interests and measures student engagement in a learning community by analyzing regular posting on the Facebook page. These posts are used to foster and encourage interactions, reflect a student’s interest and serve as reaction points from which viewers of the post convert the explicit information in the post to implicit knowledge. The data was collected over an academic year and was provided, in part, by the Google analytic reports on Facebook and self-reports of posts by members. The results support the use of active tacit knowledge activities, knowledge management and social media to enhance the student learning experience and help create the knowledge that will be used by students to construct meaning.

Keywords: constructivism, knowledge management, tacit knowledge, social media

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Authors: Gopinath Rathod, Vinod Puranik

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Growing business recognizes environmental consciousness as an important concept for survival in the competitive scenario. Environmental consciousness is a critical intersection between manufacturing and product design processes with environmental issues and concerns. This article presents a project in which quality function deployment (QFD) for environment (ECQFD) has been applied to rotary switches for enabling environmentally conscious design in the early stage of product development. ECQFD is capable of handling simultaneously the environmental and traditional product quality requirements. ECQFD consists of four phases. ECQFD phases I and II are concerned with the identification of parts that are important in enhancing environmental consciousness. ECQFD phases III and IV are concerned with the evaluation of effect of design improvement on environmental quality requirements. The case study has been practically validated which indicated the receptivity of applying ECQFD in industrial scenario.

Keywords: quality function deployment, environment, product design, design for environment, rotary switches

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Authors: Hyoshin Kim

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Most post-secondary educational institutions have offered a wide variety of professional development programs and resources in order to advance the quality of education. Such programs are designed to support faculty members by focusing on topics such as course design, behavioral learning objectives, class discussion, and evaluation methods. These are based on good intentions and might help both new and experienced educators. However, the fundamental flaw is that these ‘effective methods’ are assumed to work regardless of what we teach and whom we teach. This paper is focused on intercultural intelligence and its application to education. It presents a comprehensive literature review on context and cultural diversity in terms of beliefs, values and worldviews. What has worked well with a group of homogeneous local students may not work well with more diverse and international students. It is because students hold different notions of what is means to learn or know something. It is necessary for educators to move away from certain sets of generic teaching skills, which are based on a limited, particular view of teaching and learning. The main objective of the research is to expand our teaching strategies by incorporating what students bring to the course. There have been a growing number of resources and texts on teaching international students. Unfortunately, they tend to be based on the deficiency model, which treats diversity not as strengths, but as problems to be solved. This view is evidenced by the heavy emphasis on assimilationist approaches. For example, cultural difference is negatively evaluated, either implicitly or explicitly. Therefore the pressure is on culturally diverse students. The following questions reflect the underlying assumption of deficiencies: - How can we make them learn better? - How can we bring them into the mainstream academic culture?; and - How can they adapt to Western educational systems? Even though these questions may be well-intended, there seems to be something fundamentally wrong as the assumption of cultural superiority is embedded in this kind of thinking. This paper examines how educators can incorporate intercultural intelligence into the course design by utilizing a variety of tools such as pre-course activities, peer learning and reflective learning journals. The main goal is to explore ways to engage diverse learners in all aspects of learning. This can be achieved by activities designed to understand their prior knowledge, life experiences, and relevant cultural identities. It is crucial to link course material to students’ diverse interests thereby enhancing the relevance of course content and making learning more inclusive. Internationalization of higher education can be successful only when cultural differences are respected and celebrated as essential and positive aspects of teaching and learning.

Keywords: intercultural competence, intercultural intelligence, teaching and learning, post-secondary education

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Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

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Authors: Chris Fersterer, Col Fay, Tobias Danielmeier, Kat Achterberg, Scott Willis

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New Zealand, an island nation, has an extensive coastline peppered with small communities of iconic buildings known as Bachs. Post WWII, these modest buildings were constructed by their owners as retreats and generally were small, low cost, often using recycled material and often they fell below current acceptable building standards. In the latter part of the 20^th century, real estate prices in many of these communities remained low and these areas became permanent residences for people attracted to this affordable lifestyle choice. The Blueskin Resilient Communities Trust (BRCT) is an organisation that recognises the vulnerability of communities in low lying settlements as now being prone to increased flood threat brought about by climate change and sea level rise. Some of the inhabitants of Blueskin Bay, Otago, NZ have already found their properties to be un-insurable because of increased frequency of flood events and property values have slumped accordingly. Territorial authorities also acknowledge this increased risk and have created additional compliance measures for new buildings that are less than 2 m above tidal peaks. Community resilience becomes an additional concern where inhabitants are attracted to a lifestyle associated with a specific location and its people when this lifestyle is unable to be met in a suburban or city context. Traditional models of social housing fail to provide the sense of community connectedness and identity enjoyed by the current residents of Blueskin Bay. BRCT have partnered with the Otago Polytechnic Design School to design a new form of community housing that can react to this environmental change. It is a longitudinal project incorporating participatory approaches as a means of getting people ‘on board’, to understand complex systems and co-develop solutions. In the first period, they are seeking industry support and funding to develop a transportable and fully self-contained housing model that exploits current technologies. BRCT also hope that the building will become an educational tool to highlight climate change issues facing us today. This paper uses the Climate Safe House (CSH) as a case study for education in architectural sustainability through experiential learning offered as part of the Otago Polytechnics Bachelor of Design. Students engage with the project with research methodologies, including site surveys, resident interviews, data sourced from government agencies and physical modelling. The process involves collaboration across design disciplines including product and interior design but also includes connections with industry, both within the education institution and stakeholder industries introduced through BRCT. This project offers a rich learning environment where students become engaged through project based learning within a community of practice, including architecture, construction, energy and other related fields. The design outcomes are expressed in a series of public exhibitions and forums where community input is sought in a truly participatory process.

Keywords: community resilience, problem based learning, project based learning, case study

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Authors: Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, José Anderson Rodrigues de Souza, Jeronimo Silva Rocha

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Propagation in radio frequency is a constant concern in the application of Wireless Sensor Networks (WSN), the behavior of an environment determines how good the quality of signal reception. The objective of this paper is to analyze the behavior of a WSN in an environment for agriculture where environmental variables are present and correlate the capture of values received signal strength (RSSI) with a propagation model.

Keywords: propagation, WSN, agriculture, quality

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Authors: Mudavath Raju, Bhaskar Gugulothu, B. Rajendra Naik

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The rapid advances in Very Large Scale Integration (VLSI) technology has resulted in the reduction of minimum feature size to sub-quarter microns and switching time in tens of picoseconds or even less. As a result, the degradation of high-speed digital circuits due to signal integrity issues such as coupling effects, clock feedthrough, crosstalk noise and delay uncertainty noise. Crosstalk noise in VLSI interconnects is a major concern and reduction in VLSI interconnect has become more important for high-speed digital circuits. It is the most effectively considered in Deep Sub Micron (DSM) and Ultra Deep Sub Micron (UDSM) technology. Increasing spacing in-between aggressor and victim line is one of the technique to reduce the crosstalk. Guard trace or shield insertion in-between aggressor and victim is also one of the prominent options for the minimization of crosstalk. In this paper, far end crosstalk noise is estimated with mutual inductance and capacitance RLC interconnect model. Also investigated the extent of crosstalk in capacitive and inductively coupled interconnects to minimizes the same through shield insertion technique.

Keywords: VLSI, interconnects, signal integrity, crosstalk, shield insertion, guard trace, deep sub micron

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Authors: Abdul Basit Kiani

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Web development, the art of creating and maintaining websites, has witnessed remarkable advancements. The aim is to provide an overview of some of the cutting-edge developments in the field. Firstly, the rise of responsive web design has revolutionized user experiences across devices. With the increasing prevalence of smartphones and tablets, web developers have adapted to ensure seamless browsing experiences, regardless of screen size. This progress has greatly enhanced accessibility and usability, catering to the diverse needs of users worldwide. Additionally, the evolution of web frameworks and libraries has significantly streamlined the development process. Tools such as React, Angular, and Vue.js have empowered developers to build dynamic and interactive web applications with ease. These frameworks not only enhance efficiency but also bolster scalability, allowing for the creation of complex and feature-rich web solutions. Furthermore, the emergence of progressive web applications (PWAs) has bridged the gap between native mobile apps and web development. PWAs leverage modern web technologies to deliver app-like experiences, including offline functionality, push notifications, and seamless installation. This innovation has transformed the way users interact with websites, blurring the boundaries between traditional web and mobile applications. Moreover, the integration of artificial intelligence (AI) and machine learning (ML) has opened new horizons in web development. Chatbots, intelligent recommendation systems, and personalization algorithms have become integral components of modern websites. These AI-powered features enhance user engagement, provide personalized experiences, and streamline customer support processes, revolutionizing the way businesses interact with their audiences. Lastly, the emphasis on web security and privacy has been a pivotal area of progress. With the increasing incidents of cyber threats, web developers have implemented robust security measures to safeguard user data and ensure secure transactions. Innovations such as HTTPS protocol, two-factor authentication, and advanced encryption techniques have bolstered the overall security of web applications, fostering trust and confidence among users. Hence, recent progress in web development has propelled the industry forward, enabling developers to craft innovative and immersive digital experiences. From responsive design to AI integration and enhanced security, the landscape of web development continues to evolve, promising a future filled with endless possibilities.

Keywords: progressive web applications (PWAs), web security, machine learning (ML), web frameworks, advancement responsive web design

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Authors: Ahmed R. Althobaiti, Malcolm Munro

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Communication and effective information exchange within technology has become a crucial part of delivering knowledge to students during the learning process. It enables better understanding, builds trust, respect and increase the knowledge between students. This paper examines the communication between undergraduate students and their lecturers during the Traditional lecture and in using the Interactive Electronic Lecture System (IELS). The IELS is an application that offers a set of components, which support the effective communication between students, themselves and their lecturers. Moreover, this paper highlights the communication skills such as sender, receiver, channel and feedback. It will show how the IELS creates a rich communication environment between its users and how they communicate effectively. To examine and check the effectiveness of communication an experiment has been conducted for groups of users; students and lecturers. The first group communicated during the Traditional lecture while the second group communicated by the IELS application. The result showed that there was an effective communication between the second group more than the first group.

Keywords: communication, effective information exchange, lecture, student

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Authors: Ayomide Oyedele

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In the dynamic landscape of cybersecurity, "Strategic Cyber Sentinel" emerges as a revolutionary framework, transcending traditional approaches. This paper pioneers a holistic strategy, weaving together threat intelligence, machine learning, and adaptive defenses. Through meticulous real-world simulations, we demonstrate the unprecedented resilience of our framework against evolving cyber threats. "Strategic Cyber Sentinel" redefines proactive threat mitigation, offering a robust defense architecture poised for the challenges of tomorrow.

Keywords: cybersecurity, resilience, threat intelligence, machine learning, adaptive defenses

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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Authors: Olga Guseynova

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Being an individual activity, the memorizing process is affected to a greater degree by the individual variables; therefore, one of the decisive factors influencing the memorization is students’ individual characteristics. Based on an extensive literature study in the domains of piano education, psychology, and neuroscience, this comprehensive research was designed in order to develop three memorizing strategies that are reflective of individual students’ learning modalities (visual, kinesthetic and auditory) applied to the piano education. The design of the study required an interdisciplinary approach which incorporated the outcome of neuropsychological and pedagogic experiments. The objectives were to determine the interaction between the process of perception and the process of memorizing music; to systematize the methods of memorizing piano sheet music in accordance with the specifics of perception types; to develop Piano Memorization Inventory (PMI) and the Three Memorizing Strategies (TMS). The following research methods were applied: a method of interdisciplinary analysis and synthesis, a method of non-participant observation. As a result of literature analysis, the following conclusions were made: the majority of piano teachers and piano students participated in the surveys, had not used and usually had not known any memorizing strategy regarding learning styles. As a result, they had used drilling as the main strategy of memorizing. The Piano Memorization Inventory and Three Memorizing Strategies developed by the author of the research were based on the observation and findings of the previous researches and considered the experience of pedagogical and neuropsychological studies.

Keywords: interdisciplinary approach, memorizing strategies, perceptual learning styles, piano memorization inventory

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Authors: Prakash Singh, Piet Maphodisa Kgohlo

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Knowledge-worker productivity is one of the biggest leadership challenges facing all organizations in the twenty-first century. It cannot be denied that knowledge-worker productivity affects all organizations. The work and the workforce are both undergoing greater changes currently than at any time, since the beginning of the industrial revolution two centuries ago. Employees welcome collegial teaming (CT) as an innovative way to develop their work-integrated learning competencies. Human resource development policies must evoke the symbiotic relationship between CT and work-integrated learning, seeing that employees need to be endowed with the competence to move from one skill to another, as each one becomes obsolete, and to simultaneously develop their cognitive and emotional intelligence. The outcome of this relationship must culminate in the development of highly productive knowledge-workers. While this study focuses on teachers, the conceptual framework and the findings of this research can be beneficial for any organization, public or private sector, business or non-business. Therefore, in this quantitative study, the benefits of CT are considered in developing human resources to sustain knowledge-worker productivity. The ANOVA p-values reveal that the majority of teachers agree that CT can empower them to overcome the challenges of managing curriculum change. CT can equip them with continuous and sustained learning, growth and improvement, necessary for knowledge-worker productivity. This study, therefore, confirms that CT benefits all workers, immaterial of their age, gender or experience. Hence, this exploratory research provides a new perspective of CT in addressing knowledge-worker productivity when organizational change alters the vision of the organization.

Keywords: collegial teaming, human resource development, knowledge-worker productivity, work-integrated learning

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Authors: Rigers Dodaj

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Nowadays, the environment is a critical goal for civil engineers, human activity, construction projects, economic growth, and whole national development. Regarding the development of Albania's economy, people's living standards are increasing, and the requirements for the living environment are also increasing. Under these circumstances, environmental protection and sustainability this is the critical issue. The rising industrialization, urbanization, and energy demand affect the environment by emission of carbon dioxide gas (CO2), a significant parameter known to impact air pollution directly. Consequently, many governments and international organizations conducted policies and regulations to address environmental degradation in the pursuit of economic development, for instance in Albania, the CO2 emission calculated in metric tons per capita has increased by 23% in the last 20 years. This paper analyzes the importance of civil engineering and economic growth in the sustainability of the environment focusing on CO2 emission. The analyzed data are time series 2001 - 2020 (with annual frequency), based on official publications of the World Bank. The statistical approach with vector error correction model and time series forecasting model are used to perform the parameter’s estimations and long-run equilibrium. The research in this paper adds a new perspective to the evaluation of a sustainable environment in the context of carbon emission reduction. Also, it provides reference and technical support for the government toward green and sustainable environmental policies. In the context of low-carbon development, effectively improving carbon emission efficiency is an inevitable requirement for achieving sustainable economic and environmental protection. Also, the study reveals that civil engineering development projects impact greatly the environment in the long run, especially in areas of flooding, noise pollution, water pollution, erosion, ecological disorder, natural hazards, etc. The potential for reducing industrial carbon emissions in recent years indicates that reduction is becoming more difficult, it needs another economic growth policy and more civil engineering development, by improving the level of industrialization and promoting technological innovation in industrial low-carbonization.

Keywords: CO₂ emission, civil engineering, economic growth, environmental sustainability

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Authors: Kalina Alina Aidarovna, Khayrullina Yulia Sergeevna

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The question of forming quality housing and living environment remains a vexed problem in the current situation of high-rise apartment building in big cities of Russia. At this start up stage of the modern so-called "mass housing" market it needs to identify key quality characteristics on a different scale from apartments to the district. This paper describes the methodology of qualitative assessment of modern mass housing construction, made on the basis of the ITMO university in cooperation with the institute of spatial planning "Urbanika," based on the case study of St. Petersburg’s residential mass housing built in 2011-2014. The methodology of the study of housing and living environment goes back to the native and foreign urbanists of 60s - 80s, such Jane Jacobs, Jan Gehl, Oscar Newman, Krasheninnikov, as well as Sommer, Stools, Kohnen and Sherrod, Krasilnikova, Sychev, Zhdanov, Tinyaeva considering spatial features of living environment in a wide range of its characteristics (environmental control, territorial and personalization, privacy, etc.). Assessment is carrying out on the proposed system of criteria developed for each residential environment scale-district, quarter, courtyard, building surrounding grounds, houses, and flats. Thus the objects of study are planning unit of residential development areas (residential area, neighborhood, quarter) residential units areas (living artist, a house), and households (apartments) consisting of residential units. As a product of identified methodology, after the results of case studies of more than 700 residential complexes in St. Petersburg, we intend the creation of affordable online resource that would allow conducting a detailed qualitative evaluation or comparative characteristics of residential complexes for all participants of the construction market-developers, designers, realtors and buyers. Thereby the main objective of the rating may be achieved to improve knowledge, requirements, and demand for quality housing and living environment among the major stakeholders of the construction market.

Keywords: methodology of living environment, qualitative assessment of mass housing, scale-district, vexed problem

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Authors: Nuttha Kirdsinsap, Watchaneeporn Setthasakko

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This paper aims to gain opinions and perspectives of Certified Public Accountants (CPA) in Thailand regarding the driven force of Integrated Reporting. It employs in-depth interviews with CPA from different big 4 audits firms in Thailand, including PWC, Ernst and Young, Deloitte, and KPMG. It is found that the driven force of Integrated Reporting made CPA in Thailand awaken to the big change that is coming in the future, and it is said to be another big learning and integrating period between certified public accountants and other professionals (for example, engineers, environmentalists and lawyers), which, certified public accountants in Thailand will have to push themselves so hard to catch up.

Keywords: integrated reporting, learning, knowledge, certified public accountants, Thailand

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Authors: Albatool Al Abdulwahid, Bayan Shakally, Mariam Mohamed, Wed Almokri

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Artificial intelligence has infiltrated every part of our life and every field we can think of. With technical developments, artificial intelligence applications are becoming more prevalent. We chose ELSA speak because it is a magnificent example of Artificial intelligent applications, ELSA speak is a smartphone application that is free to download on both IOS and Android smartphones. ELSA speak utilizes artificial intelligence to help non-native English speakers pronounce words and phrases similar to a native speaker, as well as enhance their English skills. It employs speech-recognition technology that aids the application to excel the pronunciation of its users. This remarkable feature distinguishes ELSA from other voice recognition algorithms and increase the efficiency of the application. This study focused on evaluating ELSA speak application, by testing the degree of effectiveness based on survey questions. The results of the questionnaire were variable. The generality of the participants strongly agreed that ELSA has helped them enhance their pronunciation skills. However, a few participants were unconfident about the application’s ability to assist them in their learning journey.

Keywords: ELSA speak application, artificial intelligence, speech-recognition technology, language learning, english pronunciation

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Authors: Amreth Chandrasehar

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Machine Learning (ML) Models are developed and run in production to solve various use cases that help organizations to be more efficient and help drive the business. But this comes at a massive development cost and lost business opportunities. According to the Gartner report, 85% of data science projects fail, and one of the factors impacting this is not paying attention to Model Observability. Model Observability helps the developers and operators to pinpoint the model performance issues data drift and help identify root cause of issues. This paper focuses on providing insights into incorporating model observability in model development and operationalizing it in production.

Keywords: model observability, monitoring, drift detection, ML observability platform

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Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: William Li

Abstract:

Lane-change path planning is a crucial and yet complex task in autonomous driving. The traditional path planning approach based on a system of carefully-crafted rules to cover various driving scenarios becomes unwieldy as more and more rules are added to deal with exceptions and corner cases. This paper proposes to divide the entire path planning to two stages. In the first stage the ego vehicle travels longitudinally in the source lane to reach a safe state. In the second stage the ego vehicle makes lateral lane-change maneuver to the target lane. The paper derives the safe state conditions based on lateral lane-change maneuver calculation to ensure collision free in the second stage. To determine the acceleration sequence that minimizes the time to reach a safe state in the first stage, the paper proposes three schemes, namely, kinetic model based optimization, deep reinforcement learning, and 5G vehicle-to-vehicle (V2V) communications. The paper investigates these schemes via simulation. The model-based optimization is sensitive to the model assumptions. The deep reinforcement learning is more flexible in handling scenarios beyond the model assumed by the optimization. The 5G V2V eliminates uncertainty in predicting future behaviors of surrounding vehicles by sharing driving intents and enabling cooperative driving.

Keywords: lane change, path planning, autonomous driving, deep reinforcement learning, 5G, V2V communications, connected vehicles

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Authors: Sara Mota Carmo

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Wind energy applied in architecture has been largely abandoned due to the uncomfortable noise it causes. This study aims to investigate the acoustical performance in the urban environment and indoor environment of a double-skin wind energy facade. Measurements for sound transmission were recorded by using a hand-held sound meter device on a reduced-scale prototype of a wind energy façade. The applied wind intensities ranged between 2m/s and 8m/s, and the increase sound produced were proportional to the wind intensity.The study validates the acoustic performance of wind energy façade using a double skin façade system, showing that noise reduction indoor by approximately 30 to 35 dB. However, the results found that above 6m/s win intensity, in urban environment, the wind energy system applied to the façade exceeds the maximum 50dB recommended by world health organization and needs some adjustments.

Keywords: double-skin wind energy facade, acoustic energy facade, wind energy in architecture, wind energy prototype

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Authors: Soheila Sadeghi

Abstract:

Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Dalia Hanna, Alexander Ferworn

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This research provides detailed proposed training modules for the public safety teams and, specifically, SAR teams responsible for search and rescue operations related to finding lost persons with dementia. Finding a lost person alive is the goal of this training. Time matters if a lost person is to be found alive. Finding lost people living with dementia is quite challenging, as they are unaware they are lost and will not seek help. Even a small contribution to SAR operations could contribute to saving a life. SAR operations will always require expert professional and human volunteers. However, we can reduce their time, save lives, and reduce costs by providing practical training that is based on real-life scenarios. The content for the proposed training is based on the research work done by the researcher in this area. This research has demonstrated that, based on utilizing drones, the algorithmic approach could support a successful search outcome. Understanding the behavior of the lost person, learning where they may be found, predicting their survivability, and automating the search are all contributions of this work, founded in theory and demonstrated in practice. In crisis management, human behavior constitutes a vital aspect in responding to the crisis; the speed and efficiency of the response often get affected by the difficulty of the context of the operation. Therefore, training in this area plays a significant role in preparing the crisis manager to manage the emotional aspects that lead to decision-making in these critical situations. Since it is crucial to gain high-level strategic choices and the ability to apply crisis management procedures, simulation exercises become central in training crisis managers to gain the needed skills to respond critically to these events. The training will enhance the responders’ ability to make decisions and anticipate possible consequences of their actions through flexible and revolutionary reasoning in responding to the crisis efficiently and quickly. As adult learners, search and rescue teams will be approaching training and learning by taking responsibility of the learning process, appreciate flexible learning and as contributors to the teaching and learning happening during that training. These are all characteristics of adult learning theories. The learner self-reflects, gathers information, collaborates with others and is self-directed. One of the learning strategies associated with adult learning is effective elaboration. It helps learners to remember information in the long term and use it in situations where it might be appropriate. It is also a strategy that can be taught easily and used with learners of different ages. Designers must design reflective activities to improve the student’s intrapersonal awareness.

Keywords: training, OER, dementia, drones, search and rescue, adult learning, UDL, instructional design

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Authors: G. Infante Dennis, S. Balinas Elvira, C. Valencia Yolanda, Cunanan

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This paper examined the feed-backs, concerns, and insights of the teachers, supervisors, and teacher-trainers on the nature and qualities of the K-12 grade 8 design, content, approaches, and materials. Specifically, it sought to achieve the following objectives: 1) to describe the critical nature and qualities of the design, content, teaching-learning-and-evaluation approaches, and the materials to be utilized in the implementation of the grade 8 curriculum; 2) to extract the possible challenges relevant to the implementation of the design, content, teaching-learning-and-evaluation approaches, and the materials of the grade 8 curriculum in terms of the linguistic and technical competence of the teachers, readiness to implement, willingness to implement, and capability to make relevant adaptations; 3) to present essential demands on the successful and meaningful implementation of the grade 8 curriculum in terms of teacher-related factors, school-related factors, and student-related concerns.

Keywords: curriculum reforms, K-12, teacher-training, language teaching, learning

Procedia PDF Downloads 243