Search results for: cloud technologies

Authors: Mohammed Alhamed

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This research examines the factors influencing the acceptance and adoption of digital technologies in Saudi Arabia’s government sector by focusing on government employees' attitudes toward digital transformation initiatives. As digital technologies increasingly integrate into public sectors worldwide, there is a requirement to enhance citizen empowerment and government-public interactions as well as understand their impact in unique socio-political contexts like Saudi Arabia. The study aims to explore user attitudes, identify the main challenges, and investigate factors that affect the intention to use digital applications in governmental settings. The study employs a mixed-methods approach by combining quantitative and qualitative data collection to provide a comprehensive view of digital government application adoption. Data was collected through two online surveys administered to 870 government employees and face-to-face semi-structured interviews with 24 participants. This dual approach allows for both statistical analysis and thematic exploration, which provides a deeper understanding of user behaviour, perceived benefits, challenges and attitudes toward these digital applications. Quantitative data were analyzed to identify significant variables influencing adoption, while qualitative responses were coded thematically to uncover recurring themes related to user trust, security, usability and socio-political influences. The results indicate that digital government applications are largely valued for their ability to increase efficiency and accessibility and streamline processes like online documentation and inter-departmental coordination. However, the study highlights that security, privacy, and confidentiality concerns constitute substantial barriers to adoption, with participants calling for stronger cybersecurity measures and data protection policies. Moreover, usability emerged as a key theme that intuitively interfaces in encouraging adoption as respondents emphasized the importance of user-friendly. Additionally, the study found that Saudi Arabia’s unique cultural and organizational dynamics impact acceptance levels with factors like hierarchical structures and varying levels of digital literacy shaping user attitudes. A significant limitation of the study is its exclusive focus on government employees, which may limit the generalizability of the findings to other stakeholder groups, such as the general public. Despite this, the study offers valuable views for policymakers. This, in turn, suggests best practices and guidelines that could enhance the design and implementation of digital government projects. By addressing the identified barriers and leveraging the factors that drive adoption, the study underscores the potential for digital government initiatives to improve efficiency, transparency and responsiveness in Saudi Arabia's public sector. Furthermore, these findings may provide a roadmap for similar countries aiming to adopt digital government solutions within comparable socio-political and economic contexts.

Keywords: acceptance, adoption, digital technologies, digital government, Saudi Arabia

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Authors: Mohammed Nasser Al-Suqri

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Former information-seeking models are proposed more than two decades ago. These already existed models were given prior to the evolution of digital information era and Artificial Intelligence (AI) technologies. Lack of current information seeking models within Library and Information Studies resulted in fewer advancements for teaching students about information-seeking behaviors, design of library tools and services. In order to better facilitate the aforementioned concerns, this study aims to propose state-of-the-art model while focusing on the information seeking behavior of library users in the Sultanate of Oman. This study aims for the development, designing and contextualizing the real-time user-centric information seeking model capable of enhancing information needs and information usage along with incorporating critical insights for the digital library practices. Another aim is to establish far-sighted and state-of-the-art frame of reference covering Artificial Intelligence (AI) while synthesizing digital resources and information for optimizing information-seeking behavior. The proposed study is empirically designed based on a mix-method process flow, technical surveys, in-depth interviews, focus groups evaluations and stakeholder investigations. The study data pool is consist of users and specialist LIS staff at 4 public libraries and 26 academic libraries in Oman. The designed research model is expected to facilitate LIS by assisting multi-dimensional insights with AI integration for redefining the information-seeking process, and developing a technology rich model.

Keywords: artificial intelligence, information seeking, information behavior, information seeking models, libraries, Sultanate of Oman

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Authors: Nir Wittenberg, Moshe Farhi

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This mixed-methods study examines the integration of artificial intelligence (AI) tools in a first-year social work course to assess their potential for enhancing professional knowledge and skills. The incorporation of digital technologies, such as AI, in social work interventions, training, and research has increased, with the expectation that AI will become as commonplace as email and mobile phones. However, policies and ethical guidelines regarding AI, as well as empirical evaluations of its usefulness, are lacking. As AI is gradually being adopted in the field, it is prudent to explore AI thoughtfully in alignment with pedagogical goals. The outcomes assessed include professional identity, course satisfaction, and motivation. AI offers unique reflective learning opportunities through personalized simulations, feedback, and queries to complement face-to-face lessons. For instance, AI simulations provide low-risk practices for situations such as client interactions, enabling students to build skills with less stress. However, it is essential to recognize that AI alone cannot ensure real-world competence or cultural sensitivity. Outcomes related to student learning, experience, and perceptions will help to elucidate the best practices for AI integration, guiding faculty, and advancing pedagogical innovation. This strategic integration of selected AI technologies is expected to diversify course methodology, improve learning outcomes, and generate new evidence on AI’s educational utility. The findings will inform faculty seeking to thoughtfully incorporate AI into teaching and learning.

Keywords: artificial intelligence (AI), social work education, students, developing a professional identity, ethical considerations

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Authors: Henrik L. Funke, Lars Ulke-Winter, Sandra Gelbrich, Lothar Kroll

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This work reports about an approach for an automatic adaptation of concrete formulations based on genetic algorithms (GA) to optimize a wide range of different fit-functions. In order to achieve the goal, a method was developed which provides a numerical description of a fibre reinforced concrete (FRC) mixture regarding the production technology and the property spectrum of the concrete. In a first step, the FRC mixture with seven fixed components was characterized by varying amounts of the components. For that purpose, ten concrete mixtures were prepared and tested. The testing procedure comprised flow spread, compressive and bending tensile strength. The analysis and approximation of the determined data was carried out by GAs. The aim was to obtain a closed mathematical expression which best describes the given seven-point cloud of FRC by applying a Gene Expression Programming with Free Coefficients (GEP-FC) strategy. The seven-parametric FRC-mixtures model which is generated according to this method correlated well with the measured data. The developed procedure can be used for concrete mixtures finding closed mathematical expressions, which are based on the measured data.

Keywords: concrete design, fibre reinforced concrete, genetic algorithms, GEP-FC

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Authors: Mannan Mridha, Usama Gazay, Kosovare V. Aslani, Hugo Linder, Alice Ravizza, Carmelo de Maria

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In most developing countries, although the vast majority of the people are living in the rural areas, the qualified medical doctors are not available there. Health care workers and paramedics, called village doctors, informal healthcare providers, are largely responsible for the rural medical care. Mishaps due to wrong diagnosis and inappropriate medication have been causing serious suffering that is preventable. While innovators have created many devices, the vast majority of these technologies do not find applications to address the needs and conditions in low-resource settings. The primary motive is to address the acute lack of affordable medical technologies for the poor people in low-resource settings. A low cost smart medical device that is portable, battery operated and can be used at any point of care has been developed to detect breathing rate, electrocardiogram (ECG) and arterial pulse rate to improve diagnosis and monitoring of patients and thus improve care and safety. This simple and easy to use smart medical device can be used, managed and maintained effectively and safely by any health worker with some training. In order to empower the health workers and village doctors, our device is being further developed to integrate with ICT tools like smart phones and connect to the medical experts wherever available, to manage the serious health problems.

Keywords: e-health for low resources settings, health awareness education, improve patient care and safety, smart and affordable medical device

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Authors: Stefano Scippo, Damiana Luzzi, Stefano Cuomo, Maria Ranieri

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Background: In response to the rise in natural disasters linked to climate change, numerous studies on Disaster Risk Reduction Education (DRRE) have emerged since the '90s, mainly using a didactic transmission-based approach. Effective DRRE should align with an interactive, experiential, and participatory educational model, which can be costly and risky. A potential solution is using simulations facilitated by eXtended Reality (XR). Research Question: This study aims to conduct a scoping review to explore educational methodologies that use XR to enhance knowledge among teachers, students, and citizens about environmental risks, natural disasters (including climate-related ones), and their management. Method: A search string of 66 keywords was formulated, spanning three domains: 1) education and target audience, 2) environment and natural hazards, and 3) technologies. On June 21st, 2023, the search string was used across five databases: EBSCOhost, IEEE Xplore, PubMed, Scopus, and Web of Science. After deduplication and removing papers without abstracts, 2,152 abstracts (published between 2013 and 2023) were analyzed and 2,062 papers were excluded, followed by the exclusion of 56 papers after full-text scrutiny. Excluded studies focused on unrelated technologies, non-environmental risks, and lacked educational outcomes or accessible texts. Main Results: The 34 reviewed papers were analyzed for context, risk type, research methodology, learning objectives, XR technology use, outcomes, and educational affordances of XR. Notably, since 2016, there has been a rise in scientific publications, focusing mainly on seismic events (12 studies) and floods (9), with a significant contribution from Asia (18 publications), particularly Japan (7 studies). Methodologically, the studies were categorized into empirical (26) and non-empirical (8). Empirical studies involved user or expert validation of XR tools, while non-empirical studies included systematic reviews and theoretical proposals without experimental validation. Empirical studies were further classified into quantitative, qualitative, or mixed-method approaches. Six qualitative studies involved small groups of users or experts, while 20 quantitative or mixed-method studies used seven different research designs, with most (17) employing a quasi-experimental, one-group post-test design, focusing on XR technology usability over educational effectiveness. Non-experimental studies had methodological limitations, making their results hypothetical and in need of further empirical validation. Educationally, the learning objectives centered on knowledge and skills for surviving natural disaster emergencies. All studies recommended XR technologies for simulations or serious games but did not develop comprehensive educational frameworks around these tools. XR-based tools showed potential superiority over traditional methods in teaching risk and emergency management skills. However, conclusions were more valid in studies with experimental designs; otherwise, they remained hypothetical without empirical evidence. The educational affordances of XR, mainly user engagement, were confirmed by the studies. Authors’ Conclusions: The analyzed literature lacks specific educational frameworks for XR in DRRE, focusing mainly on survival knowledge and skills. There is a need to expand educational approaches to include uncertainty education, developing competencies that encompass knowledge, skills, and attitudes like risk perception.

Keywords: disaster risk reduction education, educational technologies, scoping review, XR technologies

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Authors: Fujia Yang

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Alongside technological innovation, the current “double reduction” policy and English Curriculum Standards for Compulsory Education in China both emphasise and encourage appropriately integrating educational technologies into the classroom. Therefore, schools are increasingly using digital means to engage students in English reading, but the impact of such technologies on Chinese pupils’ reading achievement remains unclear. To serve as a reference for reforming English reading education in primary schools under the double reduction policy, this study investigates the effects and primary influencing factors of a specific reading programme, Accelerated Reader (AR), on Chinese primary school students’ reading achievement. A quantitative online survey was used to collect 37 valid questionnaires from teachers, and the results demonstrate that, from teachers’ perspectives, the AR program seemed to positively affect students’ reading achievement by recommending material at the appropriate reading levels and developing students’ reading habits. Although the reading enjoyment derived from the AR program does not directly influence students’ reading achievement, these factors are strongly correlated. This can be explained by the self-paced, independent learning AR format, its high accuracy in predicting reading level, the quiz format and external motivation, and the importance of examinations and resource limitations in China. The results of this study may support reforming English reading education in Chinese primary schools.

Keywords: educational technology, reading programme, primary students, accelerated reader, reading effects

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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Authors: Woravit Kitjaroenpaiboon, Kanyarat Getkham

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This corpus analysis is a quantitative study which intended to investigate the uses of four main interactional metadiscourse devices including fourteen sub-devices in the introduction and the discussion sections of the twenty communication arts research articles taken from Online Journal of Communication and Media technologies by applying ‘AntConc’ software and PASW 18.0. The findings reveal that the three most frequently used devices in the introduction parts are attitudinal marker (adjective), booster (verb), and hedge (modal verb) while the three most frequently found devices in the discussion sections are attitudinal marker (adjective), hedge (modal verb) and booster (verb). There are nine sub-interactional metadiscourse devices among each of which significant difference exist in both introduction and discussion sections. They are attitudinal marker (adverb), attitudinal marker (adjective), booster (verb), booster (adverb), booster (adjective), hedge (modal verb), hedge (lexical verb), hedge (adverb), and hedge (adjective), while another five sub-interactional metadiscourse devices; self-mention, attitudinal marker (verb), attitudinal marker (noun), hedge (noun), and Hedge (phraseology) are found to have has no significant difference between the uses of each device in the introduction and discussion sections. The results also revealed that low and positive relationships exist among thirteen devices. One device which has no relationship with others is attitudinal marker (verb).

Keywords: corpus analysis, interactional metadiscourse devices, communication arts research articles, media technologies

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Authors: Katerina Krizova, Inigo Molina

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The ongoing climate change affects various natural processes resulting in significant changes in human life. Since there is still a growing human population on the planet with more or less limited resources, agricultural production became an issue and a satisfactory amount of food has to be reassured. To achieve this, agriculture is being studied in a very wide context. The main aim here is to increase primary production on a spatial unit while consuming as low amounts of resources as possible. In Europe, nowadays, the staple issue comes from significantly changing the spatial and temporal distribution of precipitation. Recent growing seasons have been considerably affected by long drought periods that have led to quantitative as well as qualitative yield losses. To cope with such kind of conditions, new techniques and technologies are being implemented in current practices. However, behind assessing the right management, there is always a set of the necessary information about plot properties that need to be acquired. Remotely sensed data had gained attention in recent decades since they provide spatial information about the studied surface based on its spectral behavior. A number of space platforms have been launched carrying various types of sensors. Spectral indices based on calculations with reflectance in visible and NIR bands are nowadays quite commonly used to describe the crop status. However, there is still the staple limit by this kind of data - cloudiness. Relatively frequent revisit of modern satellites cannot be fully utilized since the information is hidden under the clouds. Therefore, microwave remote sensing, which can penetrate the atmosphere, is on its rise today. The scientific literature describes the potential of radar data to estimate staple soil (roughness, moisture) and vegetation (LAI, biomass, height) properties. Although all of these are highly demanded in terms of agricultural monitoring, the crop moisture content is the utmost important parameter in terms of agricultural drought monitoring. The idea behind this study was to exploit the unique combination of SAR (Sentinel-1) and optical (Sentinel-2) data from one provider (ESA) to describe potential crop water stress during dry cropping season of 2019 at six winter wheat plots in the central Czech Republic. For the period of January to August, Sentinel-1 and Sentinel-2 images were obtained and processed. Sentinel-1 imagery carries information about C-band backscatter in two polarisations (VV, VH). Sentinel-2 was used to derive vegetation properties (LAI, FCV, NDWI, and SAVI) as support for Sentinel-1 results. For each term and plot, summary statistics were performed, including precipitation data and soil moisture content obtained through data loggers. Results were presented as summary layouts of VV and VH polarisations and related plots describing other properties. All plots performed along with the principle of the basic SAR backscatter equation. Considering the needs of practical applications, the vegetation moisture content may be assessed using SAR data to predict the drought impact on the final product quality and yields independently of cloud cover over the studied scene.

Keywords: precision agriculture, remote sensing, Sentinel-1, SAR, water content

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Authors: Husham Bayazed

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Immune responses following surgical trauma play a pivotal role in predicting postoperative outcomes from healing and recovery to postoperative complications. Postoperative complications, including infections and protracted recovery, occur in a significant number of about 300 million surgeries performed annually worldwide. Complications cause personal suffering along with a significant economic burden on the healthcare system in any community. The accurate prediction of postoperative complications and patient-targeted interventions for their prevention remain major clinical provocations. Recent Findings: Recent studies are focusing on immune dysregulation mechanisms that occur in response to surgical trauma as a key determinant of postoperative complications. Antecedent studies mainly were plunging into the detection of inflammatory plasma markers, which facilitate in providing important clues regarding their pathogenesis. However, recent Single-cell technologies, such as mass cytometry or single-cell RNA sequencing, have markedly enhanced our ability to understand the immunological basis of postoperative immunological trauma complications and to identify their prognostic biological signatures. Summary: The advent of proteomic technologies has significantly advanced our ability to predict the risk of postoperative complications. Multiomic modeling of patients' immune states holds promise for the discovery of preoperative predictive biomarkers and providing patients and surgeons with information to improve surgical outcomes. However, more studies are required to accurately predict the risk of postoperative complications in individual patients.

Keywords: immune dysregulation, postoperative complications, surgical trauma, flow cytometry

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Authors: Hossein Miri, Zhou YongQi, Chan Bormei-Suy

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The development of advanced technologies and innovative solutions has opened up exciting new possibilities for revolutionizing healthcare systems. One such emerging concept is the use of virtual and holographic health information platforms that aim to provide interactive and personalized medical information to users. This paper provides a review of notable virtual and holographic health information platforms. It begins by highlighting the need for information visualization and 3D representation in healthcare. It then proceeds to provide background knowledge on information visualization and historical developments in 3D visualization technology. Additional domain knowledge concerning holography, holographic computing, and mixed reality is then introduced, followed by highlighting some of their common applications and use cases. After setting the scene and defining the context, the need and importance of virtual and holographic visualization in medicine are discussed. Subsequently, some of the current research areas and applications of digital holography and holographic technology are explored, alongside the importance and role of virtual and holographic visualization in genetics and genomics. An analysis of the key principles and concepts underlying virtual and holographic health information systems is presented, as well as their potential implications for healthcare are pointed out. The paper concludes by examining the most notable existing mixed-reality applications and systems that help doctors visualize diagnostic and genetic data and assist in patient education and communication. This paper is intended to be a valuable resource for researchers, developers, and healthcare professionals who are interested in the use of virtual and holographic technologies to improve healthcare.

Keywords: virtual, holographic, health information platform, personalized interactive medical information

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Authors: Warachate Khobjai, Suriyan Sukati, Khemjira Jarmkom, Pattaranut Eakwaropas, Surachai Techaoei

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The propose of this study was to investigate in vitro thrombolytic activity of Zingiber cassumunar Roxb. and Prasaplai, a Thai herbal formulation of Z. cassumunar Roxb. Herbs were extracted with boiling water and concentrated by lyophilization. To observe their thrombolytic potential, an in vitro clot lysis method was applied where streptokinase and sterile distilled water were used as positive and negative controls, respectively. Crude aqueous extracts from Z. cassumunar Roxb. and Prasaplai formula showed significant thrombolytic activity by clot lysis of 17.90% and 25.21%, respectively, compared to the negative control water (5.16%) while the standard streptokinase revealed 64.78% clot lysis. These findings suggest that Z. cassumunar Roxb. exhibits moderate thrombolytic activity and cloud play an important role in the thrombolytic properties of Prasaplai formula. However, further study should be done to observe in vivo clot dissolving potential and to isolate active component(s) of these extracts.

Keywords: thrombolytic activity, clot lysis, Zingiber cassumunar Roxb., Prasaplai formula, aqueous extract

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Authors: Sang Ho Lee, Yountaik Leem

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This paper reviews Korean cases of smart cities through the analysis framework of strategic foci, characteristics and effects. Firstly, national strategies including c(cyber), e(electronic), u(ubiquitous) and s(smart) Korea strategies were considered from strategic angles. Secondly, the characteristics of smart cities in Korea were looked through the smart cities examples such as Seoul, Busan, Songdo and Sejong cities etc. from the views on the by STIM (Service, Technology, Infrastructure and Management) analysis. Finally, the effects of smart cities on socio-economies were investigated from industrial perspective using the input-output model and structural path analysis. Korean smart city strategies revealed that there were different kinds of strategic foci. c-Korea strategy focused on information and communications network building and user IT literacy. e-Korea strategy encouraged e-government and e-business through utilizing high-speed information and communications network. u-Korea strategy made ubiquitous service as well as integrated information and communication operations center. s-Korea strategy is propelling 4th industrial platform. Smart cities in Korea showed their own features and trends such as eco-intelligence, high efficiency and low cost oriented IoT, citizen sensored city, big data city. Smart city progress made new production chains fostering ICTs (Information Communication Technologies) and knowledge intermediate inputs to industries.

Keywords: Korean smart cities, Korean smart city strategies, STIM, smart service, infrastructure, technologies, management, effect of smart city

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Authors: Arash Najmaei, Jo Rhodes, Peter Lok, Zahra Sadeghinejad

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In this article, we endeavor to explore how a new business model comes into existence in the Australian cloud-computing eco-system. Findings from multiple case study methodology reveal that to develop a business model new ventures adopt a three-phase approach. In the first phase, labelled as business model ideation (BMID) various ideas for a viable business model are generated from both internal and external networks of the entrepreneurial team and the most viable one is chosen. Strategic consensus and commitment are generated in the second phase. This phase is a business modelling strategic action phase. We labelled this phase as business model strategic commitment (BMSC) because through commitment and the subsequent actions of executives resources are pooled, coordinated and allocated to the business model. Three complementary sets of resources shape the business model: managerial (MnRs), marketing (MRs) and technological resources (TRs). The third phase is the market-test phase where the business model is reified through the delivery of the intended value to customers and conversion of revenue into profit. We labelled this phase business model actualization (BMAC). Theoretical and managerial implications of these findings will be discussed and several directions for future research will be illuminated.

Keywords: entrepreneur business model, high-tech venture, resources, conversion of revenue

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Authors: James O'Farrell, Carla Weaver

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This paper examines the transformative impact of technology in higher education, particularly in the context of the post-pandemic era, focusing on the learning needs of Digital Natives (Generation Z and Generation Alpha who grew up in the digital age). The study explores how the Covid-19 pandemic accelerated the transition to online and blended learning, highlighting the challenges and opportunities this shift presented. It delves into various technological tools such as learning management systems, collaboration technologies, video platforms, game-based learning and gamification, digital libraries, and artificial intelligence, and their role in enhancing educational delivery and student engagement. The paper also addresses the need to support faculty, predominantly comprised of Digital Immigrants (people who grew up before the digital age) to integrate these technologies effectively into their teaching practices. The findings reveal that while technology has significantly improved the flexibility and accessibility of education, it also requires educators to adapt to the changing needs of Digital Natives and the evolving educational landscape. Moreover, the paper underscores the importance of safeguarding the mental health and well-being of both faculty and students, acknowledging the stress and anxiety brought about by the rapid shift in teaching and learning modalities. The study concludes with recommendations for educational institutions to create a balanced, inclusive, and supportive learning environment. This involves continuous faculty development, prioritizing mental health, and leveraging technology to bridge generational divides, thus paving the way for a resilient and innovative future in higher education.

Keywords: generation alpha, generation z, teaching strategies, technology

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Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Gaurav Kumar Sinha

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The oil refining industry, significant in its energy consumption and carbon emissions, faces increasing pressure to reduce its environmental footprint. This article explores the application of energy efficiency and sustainability analytics as crucial tools for reducing carbon emissions in oil refineries. Through a comprehensive review of current practices and technologies, this study highlights innovative analytical approaches that can significantly enhance energy efficiency. We focus on the integration of advanced data analytics, including machine learning and predictive modeling, to optimize process controls and energy use. These technologies are examined for their potential to not only lower energy consumption but also reduce greenhouse gas emissions. Additionally, the article discusses the implementation of sustainability analytics to monitor and improve environmental performance across various operational facets of oil refineries. We explore case studies where predictive analytics have successfully identified opportunities for reducing energy use and emissions, providing a template for industry-wide application. The challenges associated with deploying these analytics, such as data integration and the need for skilled personnel, are also addressed. The paper concludes with strategic recommendations for oil refineries aiming to enhance their sustainability practices through the adoption of targeted analytics. By implementing these measures, refineries can achieve significant reductions in carbon emissions, aligning with global environmental goals and regulatory requirements.

Keywords: energy efficiency, sustainability analytics, carbon emissions, oil refineries, data analytics, machine learning, predictive modeling, process optimization, greenhouse gas reduction, environmental performance

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Authors: Janusz Bedkowski, Grzegorz Kisala, Michal Wlasiuk, Piotr Pokorski

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Ground-truth data is essential for VO (Visual Odometry) and SLAM (Simultaneous Localization and Mapping) quantitative evaluation using e.g. ATE (Absolute Trajectory Error) and RPE (Relative Pose Error). Many open-access data sets provide raw and ground-truth data for benchmark purposes. The issue appears when one would like to validate Visual Odometry and/or SLAM approaches on data captured using the device for which the algorithm is targeted for example mobile phone and disseminate data for other researchers. For this reason, we propose an open source, open hardware groundtruth system that provides an accurate and precise trajectory with a 3D point cloud. It is based on LiDAR Livox Mid-360 with a non-repetitive scanning pattern, on-board Raspberry Pi 4B computer, battery and software for off-line calculations (camera to LiDAR calibration, LiDAR odometry, SLAM, georeferencing). We show how this system can be used for the evaluation of various the state of the art algorithms (Stella SLAM, ORB SLAM3, DSO) in typical indoor monocular VO/SLAM.

Keywords: SLAM, ground truth, navigation, LiDAR, visual odometry, mapping

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Authors: C. Nathanailides, S. Anastasiou, A. Dimitroglou, P. Logothetis, G. Kanlis

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In the present work we reviewed historical data of the Greek Marine aquaculture industry including adoption of new methods and technological innovation. The results indicate that the industry exhibited a rapid rise in production efficiency, employment and adoption of new technologies which reduced outbreaks of diseases, reduced production risk and the price of the farmed fish. The improvements of total quality practices and technological input on the Greek Aquaculture industry include improved survival, growth and body shape of farmed fish, which resulted from development of new aquaculture feeds and the genetic selection of the bloodstock. Also improvements in the quality of the final product were achieved via technological input in the methods and technology applied during harvesting, packaging, and transportation-preservation of farmed fish ensuring high quality of the product from the fish farm to the plate of the consumers. These parameters (health management, nutrition, genetics, harvesting and post-harvesting methods and technology) changed significantly over the last twenty years and the results of these improvements are reflected in the production efficiency of the Aquaculture industry and the quality of the final product. It is concluded that the Greek aquaculture industry exhibited a rapid growth, adoption of technologies and supply was stabilized after the global financial crisis, nevertheless, the development of the Greek aquaculture industry is currently limited by international trade sanctions, credit crunch, and increased taxation and not by limited technology or resources.

Keywords: innovation, aquaculture, total quality, management

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Authors: Innocent Uzougbo Onwuegbuzie, Siene Elizabeth Eke

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This study investigates cybersecurity challenges and solutions in managing Information and Communication Technology (ICT) at the Federal Polytechnic, Ado-Ekiti, South-West Nigeria. The rapid evolution of ICT has revolutionized organizational operations and impacted various sectors, including education, healthcare, and finance. While ICT advancements facilitate seamless communication, complex data analytics, and strategic decision-making, they also introduce significant cybersecurity risks such as data breaches, ransomware, and other malicious attacks. These threats jeopardize the confidentiality, integrity, and availability of information systems, necessitating robust cybersecurity measures. The primary aim of this research is to identify prevalent cybersecurity challenges in ICT management, evaluate their impact on the institution's operations, and assess the effectiveness of current cybersecurity solutions. Adopting a quantitative research approach, data was collected through surveys and structured questionnaires from students, staff, and IT professionals at the Federal Polytechnic, Ado-Ekiti. The findings underscore the critical need for continuous investment in cybersecurity technologies, employee and student training, and regulatory compliance to mitigate evolving cyber threats. This research contributes to bridging the knowledge gap in cybersecurity management and provides valuable insights into effective strategies and technologies for safeguarding ICT systems in educational institutions. The study's objectives are to enhance the security posture of the Federal Polytechnic, Ado-Ekiti, in an increasingly digital world by identifying and addressing the cybersecurity challenges faced by its ICT management.

Keywords: cybersecurity challenges, cyber threat mitigation, federal polytechnic Ado-Ekiti, ICT management

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Authors: Havva Tutar Kahraman, Erol Pehlivan

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In recent years, environmental pollution by wastewater rises very critically. Effluents discharged from various industries cause this challenge. Different type of pollutants such as organic compounds, oxyanions, and heavy metal ions create this threat for human bodies and all other living things. However, heavy metals are considered one of the main pollutant groups of wastewater. Therefore, this case creates a great need to apply and enhance the water treatment technologies. Among adopted treatment technologies, adsorption process is one of the methods, which is gaining more and more attention because of its easy operations, the simplicity of design and versatility. Ion exchange process is one of the preferred methods for removal of heavy metal ions from aqueous solutions. It has found widespread application in water remediation technologies, during the past several decades. Therefore, the purpose of this study is to the removal of hexavalent chromium, Cr(VI), from aqueous solutions. Cr(VI) is considered as a well-known highly toxic metal which modifies the DNA transcription process and causes important chromosomic aberrations. The treatment and removal of this heavy metal have received great attention to maintaining its allowed legal standards. The purpose of the present paper is an attempt to investigate some aspects of the use of three anion exchange resins: Eichrom 1-X4, Lewatit Monoplus M800 and Lewatit A8071. Batch adsorption experiments were carried out to evaluate the adsorption capacity of these three commercial resins in the removal of Cr(VI) from aqueous solutions. The chromium solutions used in the experiments were synthetic solutions. The parameters that affect the adsorption, solution pH, adsorbent concentration, contact time, and initial Cr(VI) concentration, were performed at room temperature. High adsorption rates of metal ions for the three resins were reported at the onset, and then plateau values were gradually reached within 60 min. The optimum pH for Cr(VI) adsorption was found as 3.0 for these three resins. The adsorption decreases with the increase in pH for three anion exchangers. The suitability of Freundlich, Langmuir and Scatchard models were investigated for Cr(VI)-resin equilibrium. Results, obtained in this study, demonstrate excellent comparability between three anion exchange resins indicating that Eichrom 1-X4 is more effective and showing highest adsorption capacity for the removal of Cr(VI) ions. Investigated anion exchange resins in this study can be used for the efficient removal of chromium from water and wastewater.

Keywords: adsorption, anion exchange resin, chromium, kinetics

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Authors: Vangelis Drosos, Dimitrios Tsoukalos, Dimitrios Tsolis

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We present a simple algorithm for capturing a 3D scene (focused on the usage of mobile device cameras in the context of augmented/mixed reality) by using a floating origin camera solution and storing the resulting information in a linear voxel octree. Data is derived from cloud points captured by a mobile device camera. For the purposes of this paper, we assume a scene of fixed size (known to us or determined beforehand) and a fixed voxel resolution. The resulting data is stored in a linear voxel octree using a hashtable. We commence by briefly discussing the logic behind floating origin approaches and the usage of linear voxel octrees for efficient storage. Following that, we present the algorithm for translating captured feature points into voxel data in the context of a fixed origin world and storing them. Finally, we discuss potential applications and areas of future development and improvement to the efficiency of our solution.

Keywords: voxel, octree, computer vision, XR, floating origin

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Authors: Madad Ali

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In the contemporary landscape of international travel, the infusion of digital technologies has given rise to innovative business models that are reshaping the dynamics of tourism. This research delves into the transformative potential of these novel business models within the realm of digital tourism and their multifaceted impact on local businesses, residents' quality of life, and the overall travel experience. The study focuses on the captivating backdrop of Yunnan Province, China, renowned for its rich cultural heritage and diverse ethnic minorities, to uncover the intricate nuances of this phenomenon. The primary objectives of this research encompass the identification and categorization of emerging business models facilitated by digital technologies, their implications on tourist engagement, and their integration into the operations of local businesses. By employing a mixed-methods approach, blending qualitative techniques like interviews and content analysis with quantitative tools such as surveys and data analysis, the study provides a comprehensive evaluation of these business models' effects on various dimensions of the tourism landscape. The distinctiveness of this research lies in its exclusive focus on Yunnan Province, China. By concentrating on Yunnan Province, the research contributes exceptional insights into the interplay between digital tourism, ethnic diversity, cultural heritage, and sustainable development. The study's outcomes hold significance for both scholarly discourse and the stakeholders involved in shaping the region's tourism strategies.

Keywords: business model, digital tourism, international travel, local businesses, quality of life

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Authors: Petra Hypšová, Martin Seitl

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One of the challenges of forensic psychology is to detect deception during a face-to-face interview. In addition to the classical approaches of monitoring the utterance and its components, detection is also sought by observing behavioral and physiological changes that occur as a result of the increased emotional and cognitive load caused by the production of distorted information. Typical are changes in facial temperature, eye movements and their fixation, pupil dilation, emotional micro-expression, heart rate and its variability. Expanding technological capabilities have opened the space to detect these psychophysiological changes and behavioral manifestations through non-contact technologies that do not interfere with face-to-face interaction. Non-contact deception detection methodology is still in development, and there is a lack of studies that combine multiple non-contact technologies to investigate their accuracy, as well as studies that show how different types of lies produced by different interviewers affect physiological and behavioral changes. The main objective of this study is to apply a specific non-contact technology for deception detection. The next objective is to investigate scenarios in which non-contact deception detection is possible. A series of psychophysiological experiments using infrared thermal imaging, eye tracking and behavioral analysis with FaceReader 9.0 software was used to achieve our goals. In the laboratory experiment, 16 adults (12 women, 4 men) between 18 and 35 years of age (SD = 4.42) were instructed to produce alternating prepared and spontaneous truths and lies. The baseline of each proband was also measured, and its results were compared to the experimental conditions. Because the personality of the examiner (particularly gender and facial appearance) to whom the subject is lying can influence physiological and behavioral changes, the experiment included four different interviewers. The interviewer was represented by a photograph of a face that met the required parameters in terms of gender and facial appearance (i.e., interviewer likability/antipathy) to follow standardized procedures. The subject provided all information to the simulated interviewer. During follow-up analyzes, facial temperature (main ROIs: forehead, cheeks, the tip of the nose, chin, and corners of the eyes), heart rate, emotional expression, intensity and fixation of eye movements and pupil dilation were observed. The results showed that the variables studied varied with respect to the production of prepared truths and lies versus the production of spontaneous truths and lies, as well as the variability of the simulated interviewer. The results also supported the assumption of variability in physiological and behavioural values during the subject's resting state, the so-called baseline, and the production of prepared and spontaneous truths and lies. A series of psychophysiological experiments provided evidence of variability in the areas of interest in the production of truths and lies to different interviewers. The combination of technologies used also led to a comprehensive assessment of the physiological and behavioral changes associated with false and true statements. The study presented here opens the space for further research in the field of lie detection with non-contact technologies.

Keywords: emotional expression decoding, eye-tracking, functional infrared thermal imaging, non-contact deception detection, psychophysiological experiment

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Authors: Feixiang Zhao, Shuangcheng Jia, Qian Li

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High-precision measurement of the target’s position and size is one of the hotspots in the field of vision inspection. This paper proposes a three-dimensional object positioning and measurement method using a monocular camera and GPS, namely the Distance Area Number-New Minimize Projection Error (DAN-NMPE). Our algorithm contains two parts: DAN and NMPE; specifically, DAN is a picture sequence algorithm, NMPE is a relatively positive optimization algorithm, which greatly improves the measurement accuracy of the target’s position and size. Comprehensive experiments validate the effectiveness of our proposed method on a self-made traffic sign dataset. The results show that with the laser point cloud as the ground truth, the size and position errors of the traffic sign measured by this method are ± 5% and 0.48 ± 0.3m, respectively. In addition, we also compared it with the current mainstream method, which uses a monocular camera to locate and measure traffic signs. DAN-NMPE attains significant improvements compared to existing state-of-the-art methods, which improves the measurement accuracy of size and position by 50% and 15.8%, respectively.

Keywords: monocular camera, GPS, positioning, measurement

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Authors: S. Karmokar

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Over the last 20 years, there has been increasing interest in the topic of entrepreneurship education as it is seen in many countries as a way of enhancing the enterprise culture and promote capability building among community. There is also rapid growth of emerging technologies across the globe and forced entrepreneurs to searching for a new model of economic growth. There are two movements that are dominating and creating waves, Technology Entrepreneurship and Social Entrepreneurship. An increasing number of entrepreneurs are awakening to the possibility of combining the scalable tools and methodology of Technology Entrepreneurship with the value system of Social Entrepreneurship–‘Transformational Entrepreneurship’. To do this transitional educational institute’s need to figure out how to unite the scalable tools of Technology Entrepreneurship with the moral ethos of Social Entrepreneurship. The traditional entrepreneurship education model is wedded to top-down instructive approaches, that is widely used in management education have led to passive educational model. Despite the effort, disruptive’ pedagogies are rare in higher education; they remain underused and often marginalized. High impact and transformational entrepreneurship education and training require universities to adopt new practices and revise current, traditional ways of working. This is a conceptual research paper exploring the potential and growth of transformational entrepreneurship, investigating links between social entrepreneurship. Based on empirical studies and theoretical approaches, this paper outlines some educational approach for both academics and educational institutes to deliver emerging transformational entrepreneurship in tertiary education. The paper presents recommendations for tertiary educators to inform the designing of teaching practices, revise current delivery methods and encourage students to fulfill their potential as entrepreneurs.

Keywords: educational pedagogies, emerging technologies, social entrepreneurship, transformational entrepreneurship

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Authors: Cam Nguyen

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Rapid, accurate, and safe sensing and imaging of physical quantities or structures finds many applications and is of significant interest to society. Sensing and imaging using radio-frequency (RF) techniques, particularly, has gone through significant development and subsequently established itself as a unique territory in the sensing world. RF sensing and imaging has played a critical role in providing us many sensing and imaging abilities beyond our human capabilities, benefiting both civilian and military applications - for example, from sensing abnormal conditions underneath some structures’ surfaces to detection and classification of concealed items, hidden activities, and buried objects. We present the developments of several sensing and imaging systems implementing RF technologies like ultra-wide band (UWB), synthetic-pulse, and interferometry. These systems are fabricated completely using RF integrated circuits. The UWB impulse system operates over multiple pulse durations from 450 to 1170 ps with 5.5-GHz RF bandwidth. It performs well through tests of various samples, demonstrating its usefulness for subsurface sensing. The synthetic-pulse system operating from 0.6 to 5.6 GHz can assess accurately subsurface structures. The synthetic-pulse system operating from 29.72-37.7 GHz demonstrates abilities for various surface and near-surface sensing such as profile mapping, liquid-level monitoring, and anti-personnel mine locating. The interferometric system operating at 35.6 GHz demonstrates its multi-functional capability for measurement of displacements and slow velocities. These RF sensors are attractive and useful for various surface and subsurface sensing applications. This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: RF sensors, radars, surface sensing, subsurface sensing

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Authors: Chih Ming Kung

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This study is an empirical study examining the enrollment rate and dropout rate of students from the perspectives of students’ learning, parents’ involvement and the learning process. Methods: Using the data collected from the entry website of Internet of Things (IoT), parents’ participation and the installation pattern of exit poll website, an investigation was conducted. Results: This study discovered that in the aspect of the degree of involvement, the attractiveness of courses, self-performance and departmental loyalty exerts significant influences on the four aspects: psychological benefits, physical benefits, social benefits and educational benefits of learning benefits. Parents’ participation also exerts a significant influence on the learning benefits. A suitable tool on the cloud was designed to collect the dynamic big data of students’ learning process. Conclusion: This research’s results can be valuable references for the government when making and promoting related policies, with more macro view and consideration. It is also expected to be contributory to schools for the practical study of promotion for enrollment.

Keywords: students’ learning factor, parents’ involvement, involvement, technology

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Authors: Fentahun Ayu Muche, Yonas Mitiku Degu

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Ethiopian farmers traditionally sow Teff seeds using the broadcasting method. However, row sowing offers higher grain yields compared to broadcasting. Despite being introduced to row sowing techniques, many farmers prefer broadcasting due to its simplicity; without proper technology, row sowing is time-consuming, labor-intensive, and physically demanding. The use of suitable row Teff seeder technologies can save time, reduce labor requirements, facilitate weed control, and increase productivity. Unfortunately, previously promoted technologies have not gained significant acceptance due to various limitations. The Agricultural Bureau of the Amhara Region, Ethiopia, has confirmed that row sowing technology significantly improves productivity, yielding results up to twice as high as traditional sowing methods. This innovative approach offers a feasible solution for enhancing Teff production in Ethiopia, contributing to greater precision and efficiency in farming practices. This research aims to design, fabricate, and test a Teff seed-cum-fertilizer drill while addressing the shortcomings of earlier technologies. During the conceptual design phase, eight alternatives were proposed, with the rail-type row Teff seed-cum-fertilizer drill selected for its technical and economic feasibility. The chosen design features five rows with adjustable spacing between 15 cm and 25 cm. It also includes an interchangeable metering mechanism for seeding rates of 5 kg/hectare and 10 kg/hectare. A key focus was placed on the metering mechanism to eliminate power transmission via ground traction, thereby mitigating performance issues caused by wheel skidding. The new design uses pinions that roll over two parallel racks suspended by four posts to transmit motion to the metering unit. Detailed analysis of the selected concept and working mechanism was conducted, and the prototype was manufactured according to specifications from the detailed design. Laboratory and field tests of the fabricated prototype demonstrated good metering mechanism efficiency, with no significant differences between rows. However, the performance of the Teff seed-cum-fertilizer drill is highly sensitive to the seed level in the hopper. Therefore, maintaining the recommended seed level is crucial for ensuring uniform seed distribution during farm operations.

Keywords: row teff planter, disc metering, scoop metering, rack and pinion, fertilizer applicator, seed drill

Procedia PDF Downloads 15