World Conference on Computer and Information Technology

This study aims to determine to what extent EU leading companies are disclosing information about the data protection policies and governance models in their annual/sustainability reports. For that purpose, we analyze the 2021 annual and sustainability reports of IBEX35, DAX30 and CAC40 companies. Additionally, we also explore the reports for the years 2016-2020 to study its evolution. The content of a total of 819 documents were automatically and manually analyzed. We try to answer the following research questions: RQ1: Are companies disclosing information about data protection in their ARs/SRs? RQ2: Are companies disclosing their data protection policies and governance models? RQ3: Do companies use data protection indicators in their reports? RQ4: What are the factors determining data protection disclosure? Our findings show a growing tendency to report about data and privacy protection, although there is a lack of standardization in such disclosure. The companies disclose more about their governance models than their data protection policies. The main indicators are those related to: Training (number of workers trained, number of hours of training provided), Queries - Claims related to incidents (loss of data, access rights, rectification, cancellation or opposition to the processing of one’s data) and Incidents related to data protection/security breaches. Moreover, we find that companies that operate in the financial sector, those that are leaders in sustainability, and those with a female presence on the board of directors are more likely to disclose information on data and privacy protection.

The Covid-19 pandemic has accelerated hybrid learning. Most educational institutions found they needed to deliver their courses or subjects through different online platforms or via printed modules to achieve learning outcomes. These learning delivery methods were effective to some but not to others as they were not able to reach their desired level of competency or mastery. To improve learning online, some educators have used game-based learning platforms to increase student interaction and engagement as well as inspire students to attain various learning goals. This study explores the use of a semi-immersive 3D virtual environment to conduct formative assessments in a gamified approach. The application used has two main components: The first utilizes an online platform where educators create and curate their assessments. An open-source general-purpose scripting language for the web and an open-source relational database management system was used to design and develop this component. The second component uses a 3D game published on mobile and the web. Students take their current assessments by entering their subject room within the virtual school. They answer each question by locating and collecting the 3D object that is being identified and putting it on its respective placeholder. The result of the activity is presented on the leaderboard. To develop the game and virtual environment, an industry-standard game engine and 3D modeling software package were used, respectively. Moving forward, a semi-virtual environment consistent with the dynamics of a post-pandemic world provides another venue to conduct effective gamified formative assessments.

The paper introduces a new IT and Telco Transport Encrypted Protocol (TEP), a patented communication protocol for transmission of information packets between physical peer’s nodes (mobile devices or networks) using blockchain paradigm, virtualization, and Artificial Intelligence (AI).

In Science, Technology, engineering, and mathematics (STEM) disciplines understanding ethical responsibilities and knowing the social impacts are as important as learning the core concepts throughout the engineering curriculum. As technology advances, the responsibilities of engineers and software developers increase to deliver high-quality products to their communities and globally. Integrating new technology without understanding its impact on society could have negative consequences. Thus, developing ethical skills is essential for computer and engineering students during college to prepare them for real-life ethical issues and how to solve them. In an object-oriented programming class at Applied Science Private University (ASU) in Jordan, real-life software-related case studies were presented to students, followed by a discussion to develop a basic understanding of ethical impacts on society. In addition, teach students the role programmers can play to prevent similar cases. The case studies were selected to cover part of the ACM code of ethics and professional conduct. Besides the ethical skills students are expected to gain, they are expected to develop an ability to think as professional programmers in critical situations and focus on the quality of their tasks and how they will impact their society and the world.

This research is based on the design and implementation of Secured Personal Data Server of Patient Medical Records in Nigeria. It is built upon the emergence of portable data server (PDS) with well secured devices that combines the security of smart cards with embedded software devices and storage capacity of NAND Flash Chips which is a novel model that is in compliance with healthcare standards in relation to data and service user-friendliness. In order to access a resource, users must meet the regulatory conditions of the policy class which is in conformity with organizational standards as stipulated by the Federal Ministry of Health in Nigeria that regularize healthcare policies. The system was designed to be flexible and adaptive in order to allow users pass on their rights of access to other users, permission given for right of access can be withdrawn based on the stipulated restrictions that have been defined in the program. The problem of inadequate healthcare facilities in producing sustainable development in Nigeria, breaches of security, delivery, confidentiality, ethical risk issues and privacy risks incurred by centralization due to privacy violations that arise from negligence, abusive use, internal and external attacks. The PDS with current server-based approach, cryptography-based and server-side secured hardware is capable of dismissing these major problems. The research specific objectives are to provide the main functionalities of a database engine that will be interoperable with existing data sources and allow secured data sharing protocols by establishing control of how users personal data are shared with others and creating a way of harmonising patient’s data from other hospitals in the country as well as beyond and also allow interoperability of clinical systems. This study adopts authentication and authorization method at inter / intra organizational levels for the security and delivery of patients’ clinical data. A stratified database with indexing and hashing techniques that can change strata without incurring a dramatic number of alterations where precomputed, relational context and Queries are executed in a pure pipeline fashion. The system will cut down substantially the cost of travelling abroad for medical consultations, which runs into billions of U.S. dollars or Naira (the Nigerian currency), especially given the poverty and related economic difficulties that Nigeria and other developing world countries face. The PDS devices are expected to assist doctors and clinicians in reviewing patients’ medical history and status prior to a consult or in reaching a diagnosis. It is also expected to provide support regarding timely referrals to and location of healthcare facilities for parallel care as needed.

In an increasingly digitized world, asynchronous systems have emerged as a foundational technology, enabling applications to scale and perform more efficiently by decoupling task execution from the main application flow. Despite their advantages, these systems pose significant challenges in state management, fault tolerance, and process traceability, often resulting in complexities that can hinder development and scalability. Workflow orchestrators have gained prominence as a solution to these challenges, providing a framework for managing the lifecycle of asynchronous tasks and workflows. This paper provides a comprehensive exploration of workflow orchestrators within asynchronous systems, analyzing their role in optimizing performance, enhancing system resilience, and simplifying development processes. Through a detailed literature review, we examine the evolution of workflow orchestrators and how they address the intricacies of asynchronous operations. We delve into the capabilities of prominent orchestrators such as Apache Airflow, Argo, Temporal, and AWS Step Functions, comparing their architectural approaches, usability, and effectiveness in various scenarios. Our findings indicate that the utilization of workflow orchestrators can lead to significant improvements in system robustness and developer efficiency. By providing insights into the operational benefits and challenges associated with each orchestrator, this study aims to aid organizations in selecting the most suitable workflow management tool, tailored to their unique requirements and existing technological ecosystems.

This paper presents an in-depth exploration of the application of Artificial Intelligence (AI), specifically Machine Learning (ML), in enhancing threat intelligence for cybersecurity applications. As cyber threats continue to evolve in complexity and sophistication, traditional cybersecurity measures struggle to keep pace. This research proposes AI-driven threat intelligence as a viable solution, leveraging the predictive and adaptive capabilities of ML to enhance threat detection and response. Our study delves into the role of ML in cybersecurity, highlighting its potential in automating and improving the accuracy of threat detection. We further explore how AI can empower cybersecurity applications, transforming them into proactive systems capable of anticipating and mitigating threats before they cause significant damage. Key findings reveal that AI-driven threat intelligence significantly improves the efficiency and effectiveness of cybersecurity applications. Our research demonstrates that ML algorithms can successfully identify patterns and anomalies that indicate potential threats, thereby enabling faster and more accurate responses. Furthermore, we propose a novel ML-based framework for threat intelligence, which shows promising results in early testing. This paper contributes to the growing body of knowledge on AI in cybersecurity, providing valuable insights for researchers, practitioners, and policymakers in the field. The findings underscore the potential of AI and ML in revolutionizing threat intelligence, paving the way for more secure digital environments.

The pandemic has caused difficulty and paved way to challenges in various areas including the educational institutions. Instruction delivery has been transformed from face to face to flexible learning that caused anxieties and distress to most role players including teachers, parents and students. Continuous spread of diseases causes face to face classes to remain not viable. Even if limited face to face classes will be allowed, online teaching is deemed to remain a practice to support instructional delivery to students. As such, learning the issues and problems being faced in online teaching especially by students is necessary to provide supervisors and administrators insights to help them plan on intervention measures to help their teachers deliver better online teaching performance for their students. Sentiment Analysis has been an interesting and popular research area encouraging researchers and practitioners to adopt this tool in various fields such as the government, health care and education. In education, instruction evaluation is one of the activities that sentiment analysis has served. Though, it is a common practice that educational institutions periodically evaluate their teachers’ performance, students’ comments which are rich in insights are not easily taken into account because of lack of automated text analytics methods. In this study, supervised machine learning algorithms were used. Experiments were conducted to evaluate base models employing naïve bayes, support vector machines, logistic regression and random forest in comparison to ensemble combining the four. Machine learning techniques such as term-frequency – inverse document frequency (TF-IDF) and ngram were also explored to devise a model with the highest possible F1 score. Results show that ensemble of the four outperformed the base models. Ngram vectorization applied with ensemble yielded highest F1 score as compared to count and tf-idf. Ngram vectorization applied with ensemble also obtained highest Cohen’s Kappa and Matthews Correlation Coefficient (MCC) and lowest Cross-Entropy indicating that it is the preferred model in sentiment classification. Meanwhile, Count vectorization applied with ensemble yielded highest Cohen’s Kappa and Matthews Correlation Coefficient (MCC) and lowest Cross Entropy Loss. Visualization techniques showed that 65.4% of the student responses were positively classified while 25.5% were negatively classified. On the other hand, 47% of the students responses were predicted to talk about instructional design/delivery, 45.3% described personality/behavior of teachers, 3.4% focused on use of technology, 2.9% on content and 1.5% on students assessment. In future work the model with highest performance measures found can be embedded in a sentiment analysis tool for students’ feedback on teaching performance. More advanced transformation techniques and other ensemble techniques may be explored to further improve performance in sentiment analysis.

Artificial intelligence applications, which are the pioneers of change in the new millennium, have declared their dominance in practices of daily living. This technology which has become more accessible to large masses especially in the past few years, has found a significant place in the business world. Artificial intelligence, which has also entered the agenda of corporate communication from management to marketing, from customer service to sales processes, shows up at many points. Robotic artificial intelligence systems which save considerable time and money create a world full of advantages. New business models that consists of productive artificial intelligence solutions support the communication processes of organizations and make the workflow easy. Thanks to the ability to imitate human thought and actions, data-driven and precise artificial intelligence systems become more reliable especially in analytical tasks instead of human resources und are considered more appealing in terms of communication by corporate executives and decision-makers. Emphasizing the importance of artificial intelligence in both the context of corporate communication and maintaining standards in consumer-oriented business processes is the main theme of this study. In this study which discusses where artificial intelligence that improves the business processes of institutions and organizations and gains a competitive advantage should be utilized more effectively in corporate communication, it is remarkable that consumer-focused business processes come into prominence. Because it is possible to achieve both customer satisfaction and personalized services through voice-activated robotic responders which were developed to find solutions to consumer issues. Artificial intelligence applications, which are an important part of the general communication model and have the ability to provide feedback and turn them into large data sets have become an important actor of the new generation of corporate communication management processes in our era. Within this context, this study addresses the importance of artificial intelligence and the application methods in corporate communication processes.

The rapid evolution of Virtual Reality (VR) technologies has instigated transformative changes in healthcare education, therapy, and patient care. This presentation provides a comprehensive overview of our suite of VR applications, created for an array of users encompassing medical practitioners, students, patients, therapists, and children with neuropsychiatric conditions. Our research, conducted across several medical universities, offers compelling evidence of VR's effectiveness in medical education. Students using VR for lung and heart auscultation training outperformed their counterparts learning via traditional methods in long-term knowledge retention and skill application. Parallel to this, we embarked on an extensive project exploring the utility of VR for children with autism spectrum disorder (ASD) and other neurodevelopmental disorders. Over 36 intensive sessions, our VR application demonstrated significant potential in enhancing essential skills such as visual tracking, pointing accuracy, and reading line retention. A noteworthy increase in parental involvement and children's engagement was also observed. These findings strongly endorse the transformative power of VR technology across healthcare spectrums. While the promising results spotlight VR's instrumental role in augmenting healthcare outcomes, they also emphasize the need for continuous research and development to further refine these digital tools. By harmonizing our dedication to innovation with meticulous scientific examination, we aim to continually enhance VR's contribution to healthcare.

The exploration of caves and their invaluable archaeological treasures has been a fascinating journey into the depths of history. As technology continues to evolve, new methodologies have emerged to shed light on these enigmatic subterranean worlds. This conference presentation delves into the application of a pioneering 3D scanning research method on cave archaeology, with a focus on the Bihor Caves, scanned in late June and early July 2023, as a case study. The presentation revolves around the successful execution of 3D scanning techniques, allowing for a comprehensive documentation of the cave's intricate features, artifacts, and geological formations. By leveraging cutting-edge scanning equipment and software, an accurate digital representation of the cave's interior has been generated, providing a detailed visual record of its historical significance. The presentation also highlights the challenges encountered during the scanning process and the solutions devised to overcome them, offering insights for future research in cave archaeology. The analysis of the scanned data has already begun to reveal intriguing patterns, allowing for the development of hypotheses regarding the cave's historical use, inhabitants, and cultural context.

Remote work has increasingly integrated into the daily routines of employees whose tasks are conducive to remote completion and do not necessitate physical presence at the workplace. This shift was particularly evident during the COVID-19 pandemic, wherein widespread restrictions compelled a substantial portion of the global workforce to operate remotely. However, this transition also unveiled vulnerabilities, notably in cybersecurity, as remote work setups often lacked the fortified network perimeters typical of physical office environments. This paper aims to augment the established “CIA Triad” supplementary components tailored to contemporary cybersecurity demands, particularly within the context of remote work arrangements organized by businesses. The researchers intend to examine existing alterations of the CIA triad put forth by various researchers and standards organizations. Through the assessment of these adaptations, they aim to enhance and expand upon the most comprehensive iteration of the CIA model by incorporating socio-technical elements to encompass the previously underemphasized facets of cybersecurity. Drawing upon insights from prior research, the researchers will identify the most suitable form of socio-technical model adjustments that comprehensively tackle cybersecurity challenges, particularly in bolstering the security posture of remote workers. Consequently, the researchers' newly developed model seeks to emphasize and fortify cybersecurity policies crucial to remote work environments, ultimately providing an optimal blend of strategies to enhance the security of remote teams.