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The motivation to perform research on feedback control system for unmanned aerial vehicles, a fact that each quadrocopter is unstable.

For this reason, it is necessary to design a control system which is capable of making unmanned aerial vehicle vertical take-off and landing (UAV VTOL) stable and controllable. For this purpose, it was decided to use a feedback control system with cascaded PID controller. The main reason for using it was that PID controllers are simple to implement and do not use much hardware resources. Moreover, cascaded control systems allow to control object response using more parameters than in a standard PID control. STM32 microcontrollers were used to make a real control system. The rapid prototyping using Embedded Coder Toolbox, FreeRTOS and STM32 CubeMX was conducted to design the algorithm of the feedback control system with cascaded PID controller for unmanned aerial vehicle vertical take-off and landings (UAV VTOLs).

During research, an algorithm of UAV VTOL control using the feedback control system with cascaded PID controller was designed. Tests were performed for the designed algorithm in the model simulation in Matlab/Simulink and in the real conditions.

It has been proved that an additional control loop must have a full PID controller. Moreover, a new library is presented for STM32 microcontrollers made using the Embedded Coder Toolbox just for the research. This library enabled to use rapid prototyping while developing the control algorithms.

The purpose of this paper is to derive a taxonomy of business models used by start-up firms that rely on data as a key resource for business, namely data-driven business models (DDBMs). By providing a framework to systematically analyse DDBMs, the study provides an introduction to DDBM as a field of study.

To develop the taxonomy of DDBMs, business model descriptions of 100 randomly chosen start-up firms were coded using a DDBM framework derived from literature, comprising six dimensions with 35 features. Subsequent application of clustering algorithms produced six different types of DDBM, validated by case studies from the study’s sample.

The taxonomy derived from the research consists of six different types of DDBM among start-ups. These types are characterised by a subset of six of nine clustering variables from the DDBM framework.

A major contribution of the paper is the designed framework, which stimulates thinking about the nature and future of DDBMs. The proposed taxonomy will help organisations to position their activities in the current DDBM landscape. Moreover, framework and taxonomy may lead to a DDBM design toolbox.

This paper develops a basis for understanding how start-ups build business models capture value from data as a key resource, adding a business perspective to the discussion of big data. By offering the scientific community a specific framework of business model features and a subsequent taxonomy, the paper provides reference points and serves as a foundation for future studies of DDBMs.

Digital learning has become a global trend. Partly or fully automatic learning systems are integrated into education in schools and universities on a previously unseen scale. Learning systems have a lot of potential for re-education, life-long learning and for increasing access to educational resources. Learning systems create massive amounts of data about learning behaviour. Analysing that data for educational decision making has become an important track of research. The purpose of this paper is to analyse data from an intermediate-level computer science course, which was taught to 141 students in spring 2018 at University of Turku, Department of Future Technologies, Finland.

The available variables included number of submissions, submission times, variables of groupwork and final grades. Associations between these variables were looked at to reveal patterns in students’ learning behaviour.

It was found that time usage differs per different grades so that students with grade 4 out of 5 used most time. Also, it was found that studying at night is connected to weaker learning outcomes than studying during daytime. Several issues in relation to groupwork were revealed. For example, associations were found between prior skills, preference for individual vs groupwork, and course learning outcomes.

The research was limited by the domain of available variables, which is a common limitation in learning analytics research.

The practical implications include important ideas for future research and interventions in digital learning.

The importance of research on soft skills, social skills and collaboration is highlighted.

The paper points a number of important ideas for future research. One important observation is that some research questions in learning analytics need qualitative approaches, which need to be added to the toolbox of learning analytics research.

This study uses Hall's (1976) theory of low/high context culture with theories of interpersonal adaptation (Gudykunst, 1985; Patterson, 1983) to test communication preferences, flexibility, and effectiveness in same‐ and mixed‐culture negotiation. Ninety‐three same‐culture low context (Israel, Germany, Sweden, and U.S.), 101 same‐culture high context (Hong Kong, Japan, Russia, Thailand), and 48 mixed‐culture mixed context (U.S.‐Japan, U.S.‐Hong Kong) dyads negotiated a 1 ½ hour simulation. Transcripts were content coded for direct and indirect integrative sequences and analyzed with hierarchical linear regression. Supporting the theory, results revealed more indirect integrative sequences in high context dyads and more direct integrative sequences in low context and mixed context dyads. Direct integrative sequences predicted joint gains for mixed context dyads.

The purpose of this paper is to provide instructional guidance on how to increase validity and reduce subjectivity in qualitative studies, such as grounded theory. The paper also demonstrates how different techniques can help management research by including informants/managers in a time efficient way.

This paper describes how three complementary triangulation methods can be used for validation and exploration of concepts and themes in qualitative studies. Tree graphs, concept mapping, and member checking are applied in a managerial case study, complementing a conventional grounded theory approach.

The paper suggests that naturalistic inquiries, such as grounded theory and thematic analysis, can use mixed methods and multiple sources and coders in order to offset biases and to validate and sort findings. The case study presents three different perspectives on how an organization comprehends diversity as a strategic issue.

The paper suggests a mixed methods design that addresses some of the potential shortcomings often found in grounded theory and other qualitative studies, their theory development and their documentation of processes. It positions the approach over the range of the triangulation literature and it argues that it is important to be aware of different triangulation mindsets, and these they are not necessarily contradictory.

The Metaverse is rapidly reshaping the understanding of tourism, yet the public perception of this new domain remains largely uncharted empirically. This paper aims to build on the technology acceptance model (TAM) and diffusion of innovations theory (DIT) to fill this gap, offering crucial insights that could inform scholars and practitioners in both the tourism and technology sectors.

Using a big-data approach, the authors applied machine learning to scrape comments made by social media users on recent popular posts or videos related to tourism in the Metaverse from three prominent social media platforms. The cleaning process narrowed down 15,461 comments to 2,650, which were then analysed using thematic, emotion and sentiment analysis techniques.

The thematic analysis revealed that virtual tourism evokes a complex range of public beliefs. While many express awe and excitement toward its immersive capabilities, others remain sceptical about authenticity compared to physical travel. Additional themes show people draw comparisons to real-world tourism, discuss technology’s role and note educational value and novelty. However, some comments raise concerns about potential societal harms, exploitation and mental health impacts. Sentiment analysis found over half of the comments positive, though some were negative. Emotion analysis showed contentment, happiness and excitement as most frequent, though sadness, worry and loneliness also featured. Overall, perceptions of Metaverse tourism encompass enthusiasm yet substantial ambivalence.

To the best of the authors’ knowledge, this study is one of the first to comprehensively analyse public discussions on Metaverse tourism. It takes TAM and Rogers’s DIT a step further and provides fresh insights into how these theories can be employed in the emerging field of Metaverse tourism. The themes revealed new conceptual insights into multidimensional factors shaping public beliefs about Metaverse tourism and thus informing scholarly research on virtual interaction and technology acceptance regarding Metaverse tourism. In addition, the results can help tourism providers, platforms and marketers address salient public beliefs and sentiments/attitudes in developing marketing offerings, experiences and communications. Over time, this analysis methodology can be used to track the evolving public perceptions of Metaverse tourism.

One of the main obstacles facing project-based learning (PBL) adoption relates to a lack of understanding by teachers and students in the roles they are required to play in the learning process. This study aims to address this obstacle, so as to better promote regular adoption of PBL pedagogy in educational institutions.

The strategy was to undertake an in-depth case study of PBL courses taught in UNI-X’s undergraduate curriculum. The case study approach is particularly appropriate for this exploratory study because it allows to capture the organizational dynamics of the phenomenon better and also its ability to explain the phenomenon based on interpretation of data.

This paper presents an empirical study on the role perspective of PBL in a collaborative project environment. By drawing upon a case study of UNI-X, the authors argue that a teacher plays the roles of a designer, champion, facilitator and manager in a PBL course. To ensure that learning is effective, students should play the roles of a self-directed learner and a warrior when completing their projects. It is clear that role ambiguity and role conflict could occur in PBL courses and might even impact the effectiveness of student learning.

For researchers, this paper contributes to the PBL literature by introducing a role perspective of PBL. This study identifies a list of roles a teacher and a student could potentially play in a PBL setting. Such understanding could serve as a reminder for a teacher and a student for the roles they need to play in achieving learning outcomes of a PBL course.

The purpose of this paper is to implement a finite set model predictive control algorithm to a shunt (or parallel), multilevel (cascaded H-bridge) active power filter (APF). Specifically, the purpose is to get a controller that could compensate the mains current and, at the same time, to control the voltages of its capacitors. This strategy avoids the use of multiple PWM carriers or another type of special modulator, and requires a relatively low processing power.

This paper is focussed in the application of the predictive controller to a single-phase parallel APF composed for two H-bridges connected in series. The same methodology can be applied to a three-phase APF. In the DC buses of each H-bridge, a floating capacitor was connected, whose voltage is regulated by the predictive controller. The controller is composed by, first, a model for the charge/discharge dynamics for each floating capacitor and a model for the output current of the APF; second, a cost function; and third, an optimization algorithm that is able to control all these variables at the same time, choosing in each sample period the best combination of firing pulses.

The controller can track the voltage references, compensate the current harmonics and compensate reactive power with an algorithm that evaluates only the three nearest voltage levels to the last voltage level applied in the inverter. This strategy decreases the number of calculations required by the predictive algorithm. This controller can be applied to the general case of a single-phase multilevel APF of N-levels and extend it to the three-phase case without major problems.

The implemented controller, when the authors consider a constant sample time, gives a mains current with a Total Harmonic Distortion (THD-I) slightly greater in comparison with the base algorithm (that evaluates all the voltage levels). However, when the authors consider the processing times under the same processor, the implemented algorithm requires less time to get the optimal values, can get lower sampling times and then a best performance in terms of THD-I. To implement the controller in a three-phase APF, a faster Digital Signal Processor would be required.

The implemented solution uses a model for the charge/discharge of the capacitors and for the filter current that enable to operate the cascaded multilevel inverter with asymmetrical voltages while compensates the mains currents, with a predictive algorithm that requires a relatively low amount of calculations.

Qualitative research suffers from “contestation” and a lack of “boilerplate” problems to assessing and presenting qualitative data, which have hampered its development and the broader acceptance of qualitative research. This paper aims to address this gap by marrying the constructivist methodology and RQDA, a relatively new open-source computer-assisted qualitative data analysis (CAQDAS)-based R extension and demonstrate how the software can increase the rigor, transparency and validity of qualitative research.

This paper highlights the constructivist approach as an important paradigm in qualitative research and demonstrates how it can be operationalized and enhanced using RQDA. It provides a technical and methodological review of RQDA, along with its main strengths and weaknesses, in relation with two popular CAQDAS tools, ATLAS.ti and NVivo. Using samples of customer-generated e-complaints and e-praises in the electronics/computer sector, this paper demonstrates the development of a process model of customer e-complaint rhetoric.

This study offers step-by-step instructions for installing and using RQDA for data coding, aggregation, plotting and theory building. It emphasizes the importance of techniques for sharing coding outputs among researchers and journal gatekeepers to better disseminate and share research findings. It also describes the authors’ use of RQDA in classrooms of undergraduates and graduate students.

This paper addresses the “contestation” and “boilerplate” gaps, offering practical, step-by-step instructions to operationalize and enhance the constructivist approach using the RQDA-based approach. This opens new opportunities for existing R users to “cross over” to analyzing textual data as well as for computer-savvy scholars, analysts and research students in academia and industry who wish to transition to CAQDAS-based qualitative research because RQDA is free and can leverage the strengths of the R computing platform.

This study offers the first published review and demonstration of the RQDA-based constructivist methodology that provide the processes needed to enhance the rigor, transparency and validity of qualitative research. It demonstrates the systematic development of a data structure and a process model of customer e-complaint rhetoric using RQDA.

The paper aims to present an outline how libraries are harnessing browser extensions to provide an easy and convenient access to library resources and services. Investigating the features, purposes of use and types of browser extensions prevalent among libraries in different regions, the paper seeks to measure the degree of implementation of browser extensions.

Stratified sampling method was followed to select academic libraries, and convenient sampling method was applied to select public libraries from four continents – Asia, Oceania, Europe and North America. Two-step web content analysis was applied to gather data along the select dimensions.

The study contributes to the recent advances in application of browser extension with numerous examples focussing on the relevance of different approaches adopted by the libraries. Providing a framework of proportionate implementation along checkpoints, the study also highlights degree of acceptance of browser extension among libraries in different regions.

The investigation was restricted to libraries having English websites and confined to four continents only. This study aims at improving understanding among the librarians about the intended use and application of browser extension and helping them benchmark their effort in support of education, research and training. The current investigation expands the scope of future research on remaining regions and website whose contents are in non-English language to attain a broader perspective of its implementation.

The article may guide library professionals to use, develop and promote the implementation of browser extension in libraries. The checkpoints used here may serve as bedrock for framing questionnaire and interview schedule for conducting future research examining users’ perception of browser extension in the context of library resources and usage pattern, to fully comprehend its practicability and usefulness.