Reviewerly/exHarmony huggingface dataset:
Autonomous Underwater Vehicles: Identifying Critical Issues and Future Perspectives in Image Acquisition

Underwater imaging has been present for many decades due to its relevance in vision and navigation systems. In recent years, advances in robotics have led to the availability of autonomous or unmanned underwater vehicles (AUVs, UUVs). Despite the rapid development of new studies and promising algorithms in this field, there is currently a lack of research toward standardized, general-approach proposals. This issue has been stated in the literature as a limiting factor to be addressed in the future. The key starting point of this work is to identify a synergistic effect between professional photography and scientific fields by analyzing image acquisition issues. Subsequently, we discuss underwater image enhancement and quality assessment, image mosaicking and algorithmic concerns as the last processing step. In this line, statistics about 120 AUV articles fro recent decades have been analyzed, with a special focus on state-of-the-art papers from recent years. Therefore, the aim of this paper is to identify critical issues in autonomous underwater vehicles encompassing the entire process, starting from optical issues in image sensing and ending with some issues related to algorithmic processing. In addition, a global underwater workflow is proposed, extracting future requirements, outcome effects and new perspectives in this context.
Constructing a disease database and using natural language processing to capture and standardize free text clinical information

The ability to extract critical information about an infectious disease in a timely manner is critical for population health research. The lack of procedures for mining large amounts of health data is a major impediment. The goal of this research is to use natural language processing (NLP) to extract key information (clinical factors, social determinants of health) from free text. The proposed framework describes database construction, NLP modules for locating clinical and non-clinical (social determinants) information, and a detailed evaluation protocol for evaluating results and demonstrating the effectiveness of the proposed framework. The use of COVID-19 case reports is demonstrated for data construction and pandemic surveillance. The proposed approach outperforms benchmark methods in F1-score by about 1-3%. A thorough examination reveals the disease's presence as well as the frequency of symptoms in patients. The findings suggest that prior knowledge gained through transfer learning can be useful when researching infectious diseases with similar presentations in order to accurately predict patient outcomes.
Emerging trends and research focal points of information technologies for financial control and accounting at the state and corporate level: Bibliometric research and visualization

The rapid development of information technologies poses challenges to various processes of the financial departments of companies or the state. The aim of the paper is to substantiate the main directions of global research on information technologies for financial control and accounting for a better perception and derivation of the potentially associated requirements, challenges, and risks under the evolutionary magnifier. Applied bibliometric and network analysis, comprising analytical and visualization tools of Scopus and VosViewer, reveals the constantly increasing research interests of scholars in the field of research that has reached its maximum in 2022 and continues to rise, especially in the countries with the frontrunner affiliations (the United States, China, and the United Kingdom). The cluster analysis identified 19 total thematic clusters, eleven at the state and eight at the corporate levels, that determined the focal research points Big Data, Blockchain, and Artificial Intelligence are similar for financial control and accounting at the state and corporate level and underlined the partial similarity in terms of technical specification (cryptocurrency) as well as differences in specific levels (social networking issues at the state level) that are reflected in the recommendations for the elaboration of significant technology interfaces for both levels under investigation.
Similarities and Differences between Immersive Virtual Reality, Real World, and Computer Screens: A Systematic Scoping Review in Human Behavior Studies

In the broader field of human behavior studies, there are several trade-offs for on-site experiments. To be tied to a specific location can limit both the availability and diversity of participants. However, current and future technological advances make it possible to replicate real-world scenarios in a virtual environment up to a certain level of detail. How these differences add up and affect the cross-media validity of findings remains a topic of debate. How a virtual world is accessed, through a computer screen or a head-mounted display, may have a significant impact. Not surprisingly, the literature has presented various comparisons. However, while previous research has compared the different devices for a specific research question, a systematic review is lacking. To fill this gap, we conducted this review. We identified 1083 articles in accordance with the PRISMA guidelines. Following screening, 56 articles remained and were compared for a qualitative synthesis to provide the reader a summary of current research on the differences between head-mounted displays (HMDs), computer screens, and the real world. Overall, the data show that virtual worlds presented in an HMD are more similar to real-world situations than to computer screens. This supports the thesis that HMDs are more suitable than computer screens for conducting experiments in the field of human behavioral studies.
Privacy-Preserving Blockchain Technologies

The main characteristics of blockchains, such as security and traceability, have enabled their use in many distinct scenarios, such as the rise of new cryptocurrencies and decentralized applications (dApps). However, part of the information exchanged with the typical blockchains is public, which can lead to privacy issues. To avoid or mitigate these issues, some blockchains are applying mechanisms to deal with data privacy. Trusted Execution Environments, the basis of confidential computing, and secure Multi-party Computation are two technologies that can be applied in that sense. In this paper, we analyzed seven blockchain technologies that apply mechanisms to improve data privacy. We defined seven technical questions related to common requirements for decentralized applications and, to answer each question, we reviewed the available documentation and gathered information from chat channels. We briefly present each blockchain technology and the answers to each technical question. Finally, we present a table summarizing the information and showing which technologies are more prominent.
Factors Influencing Customer Satisfaction on E-Banking Services: A Study of Libyan Banks

This study aimed to investigate the factors influencing customer satisfaction with e- banking services in Libyan banks, with a focus on perceived usefulness, perceived ease of use, perceived credibility, and customer attitude. A descriptive research design with a quantitative research approach was used, and data was collected through a questionnaire distributed online to 215 e-banking users. The findings revealed that perceived usefulness, perceived ease of use, perceived credibility, and customer attitude have a significant positive impact on customers' satisfaction with e-banking services. Customer attitude was found to be the most important factor, followed by perceived ease of use, perceived credibility, and perceived usefulness. The results of this study can be useful for banks in Libya in improving their e- banking services to enhance customers' satisfaction. Banks should prioritize improving customer attitudes towards e-banking services, followed by enhancing the ease of use and credibility of their platforms. Banks should also consider promoting the perceived usefulness of their e-banking services to further increase customer satisfaction. By taking these actions, banks can attract and retain more customers while staying competitive in the digital age. Additionally, these findings can contribute to the existing literature on e-banking services and customer satisfaction, providing valuable insights for future research.
Understanding Curriculum Transformation Towards Educational Innovation in The Era of All-Digital Technology

Through a study of several curriculum kinds of literature and educational innovations, we have understood how curriculum change in various educational institutions is. This study analyzed and discusses how policymakers prepare various strategic policies, from government documents to schools. We reviewed all documents with a phenomenological approach from curriculum transformation policy documents, from central institutional and local internal schools expecting school involvement with the change towards transformation. With curriculum transformation positioned as an innovation in a challenging digital era, the theory and application of transformational learning encourage the lens to analyze the alignment of national policies with the goal of curriculum transformation. This paper explores the extent to which the government is changing from a high-risk, subject-content-based learning approach to the curriculum. Pedagogy of learning and applications was essential to achieve more complex educational goals and active learning theory. Three phases of commitment are distinguished through an assessment rubric, offering a system for evaluating educational plan change drives. Suggestions for instructive pioneers incorporate the need to coordinate institutional techniques with disciplinary mastery and ability and the significance of language reception as a forerunner to execution.
IoT Device Identification Using Unsupervised Machine Learning

Device identification is a fundamental issue in the Internet of Things (IoT). Many critical services, including access control and intrusion prevention, are built on correctly identifying each unique device in a network. However, device identification faces many challenges in the IoT. For example, a common technique to identify a device in a network is using the device’s MAC address. However, MAC addresses can be easily spoofed. On the other hand, IoT devices also include dynamic characteristics such as traffic patterns which could be used for device identification. Machine-learning-assisted approaches are promising for device identification since they can capture dynamic device behaviors and have automation capabilities. Supervised machine-learning-assisted techniques demonstrate high accuracies for device identification. However, they require a large number of labeled datasets, which can be a challenge. On the other hand, unsupervised machine learning can also reach good accuracies without requiring labeled datasets. This paper presents an unsupervised machine-learning approach for IoT device identification.
A Software Factory for Accelerating the Development of Recommender Systems in Smart Tourism Mobile Applications: An Overview

Recommender Systems (RSs) have become essential for suggesting personalized recommendations to users across various fields, especially in tourism. Due to the rising popularity of mobile devices, mobile RSs have emerged as a potential research area. However, developing these systems into smart tourism mobile applications requires a significant investment in artificial intelligence experts and software engineering. Hence, to reduce the cost of this investment, we propose building a software factory that provides a robust set of assets such as domain-specific languages for accelerating the development process. To this aim, we apply a model-driven engineering approach that uses models, metamodels, and model transformations to support the designing and implementation of these software systems. In this paper, we introduce an overview of our software factory to support the development of several models of RSs.
An Advanced Crow Search Algorithm for Solving Global Optimization Problem

The conventional crow search (CS) algorithm is a swarm-based metaheuristic algorithm that has fewer parameters, is easy to apply to problems, and is utilized in various fields. However, it has a disadvantage, as it is easy for it to fall into local minima by relying mainly on exploitation to find approximations. Therefore, in this paper, we propose the advanced crow search (ACS) algorithm, which improves the conventional CS algorithm and solves the global optimization problem. The ACS algorithm has three differences from the conventional CS algorithm. First, we propose using dynamic AP (awareness probability) to perform exploration of the global region for the selection of the initial population. Second, we improved the exploitation performance by introducing a formula that probabilistically selects the best crows instead of randomly selecting them. Third, we improved the exploration phase by adding an equation for local search. The ACS algorithm proposed in this paper has improved exploitation and exploration performance over other metaheuristic algorithms in both unimodal and multimodal benchmark functions, and it found the most optimal solutions in five engineering problems.
Fundamental limits of pulsed quantum light spectroscopy: Dipole moment estimation

In order to rigorously find the limit of estimation precision for an atom probed by a quantum light pulse, the authors incorporate tools from quantum metrology and atomic spectroscopy. Their methodology uses a Hamiltonian model of the light-matter interaction to compute the information in the quantum state of the light after interaction with the atom.
A systematic literature review on pharmaceutical supply chain: research gaps and future opportunities

Recently, blockchain has increasingly been used in several sectors as the technological underpinning for providing a secure and reliable environment. It has been used in a few sectors for provenance of high-value products. In this paper, we focus on the pharmaceutical sector in which the need for drug provenance is crucial due to counterfeiting and for finding efficient ways to handle drug waste. The focus on this paper is two-fold. The first contribution is to review the existing literature critically and systematically on blockchain use in the pharmaceutical sector. We identify four crucial factors that are critical in the pharmaceutical sector. Subsequently, we systematically review the existing literature on blockchain use in the pharmaceutical sector. The second contribution is based on the analysis of the existing literature, we identify key research gaps on blockchain use in the pharmaceutical sector. Finally, an intelligent platform is proposed to address the identified gaps.
Enhancing adaptive learning: leveraging interactive exercises through the LearningApps service

The article explores the potential of adaptive learning systems in promoting optimal intellectual development for individual students based on their natural abilities and inclinations. It examines the key benefits of incorporating interactive exercises into educational activities through the utilization of the LearningApps service’s technical capabilities. The paper showcases how this service can be effectively employed to implement a personalized approach to education. Furthermore, it presents the empirical findings from a study that investigated the integration of the LearningApps service in the educational process of first-year students studying psychological disciplines. The statistical data obtained from the study demonstrates the effectiveness and relevance of using the LearningApps service in enhancing the motivational component of professional training for future professionals within the context of adaptive learning.
Using a mobile application to teach students to measure with a micrometer during remote laboratory work

In modern conditions, the transition to distance learning has set new tasks for teachers, in particular, related to laboratory work. In these works, students not only study the structure and features of special equipment, but also acquire practical skills in working with the tool. The purpose of the article is to present our own experience of developing and using in the educational process a mobile application for teaching micrometer measurements during the relevant remote laboratory work in the disciplines ``Interchangeability, Standardization and Technical Measurements'' and ``Physics''. The literature analysis showed that ICT is widely used in the educational process in higher education, but computer programs and mobile applications are usually developed for secondary school disciplines, so there was a need to develop an information program for teaching students in distance learning, in particular during laboratory work. In order to teach students to work with a micrometer during distance learning, we have developed a mobile application. The process of developing the application included modeling the micrometer in the CAD system, creating training scenes in the Unity game engine and writing scripts to fully immerse students in the learning process. The mobile application developed by us consists of three parts: theoretical, educational and practical. In the theoretical part, students learn the structure and principles of working with a micrometer. The training part is developed in the form of a video lesson of working with the equipment. The practical part contains an electronic model of the micrometer and allows you to make measurements. Thus, during distance learning using the developed application, the percentage of qualitative success of students in laboratory work on the topic ``Measuring parts with a micrometer'' increased by 7.3\% compared to the same period of distance learning without the use of this application.
Major benefits of using smart technologies in education

This research considers the features of applying smart-learning technologies in education that provide future-qualified specialists with the necessary skills for the implementation of successful professional activities in the conditions of a digital society. The relevance of the study is conditioned upon the need to find the main advantages of smart education in educational institutions. The purpose of the research is to determine the benefits of using smart technologies in education and the abilities that students should master to meet the needs of modern society. The author attempts to use a set of interconnected theoretical research methods to achieve the purpose and present the examined subject comprehensively, including the method of critical analysis of scientific literature, which contributed to the description of the purposes and specifics, the possibility and benefits of using smart-learning technologies and drawing conclusions, and the method of examining and summarising the experiences of other countries, which allowed concluding. It was identified that for various entities and educational situations, the meaning of “smart” has different definitions. It has been established that fundamental content changes are occurring, which makes the modern educational system smart in the majority of countries around the world. It was determined that using smart-learning technologies opens up many new opportunities in education, which improve the concentration of students’ attention, accelerate the assimilation of educational material, and, as a result, increase the success rate of each student. Based on research, four levels of abilities in smart education that students should master to meet the needs of modern society have been proposed. The main advantages of using smart learning in the educational process are described. The most common are the continuity of the educational process and the integrity of educational information; mobility; the student’s autonomy. The research can be useful for specialists in educational institutions and teachers to improve the professional training of specialists.
On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks

Classical algorithms are often not effective for solving nonconvex optimization problems where local minima are separated by high barriers. In this paper, we explore possible quantum speedups for nonconvex optimization by leveraging the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>g</mml:mi><mml:mi>l</mml:mi><mml:mi>o</mml:mi><mml:mi>b</mml:mi><mml:mi>a</mml:mi><mml:mi>l</mml:mi></mml:math> effect of quantum tunneling. Specifically, we introduce a quantum algorithm termed the quantum tunneling walk (QTW) and apply it to nonconvex problems where local minima are approximately global minima. We show that QTW achieves quantum speedup over classical stochastic gradient descents (SGD) when the barriers between different local minima are high but thin and the minima are flat. Based on this observation, we construct a specific double-well landscape, where classical algorithms cannot efficiently hit one target well knowing the other well but QTW can when given proper initial states near the known well. Finally, we corroborate our findings with numerical experiments.
DIGITALIZATION OF THE EDUCATIONAL PROCESS IN THE CONDITIONS OF DISTANCE LEARNING IN HIGHER EDUCATION INSTITUTIONS

Digitalization of the educational process of higher education institutions is considered as a leading direction of improving the effectiveness of education, one of the main factors improving the quality of the educational process, which solves theoretical and practical problems of higher education, patterns, principles, forms, methods, technologies, content, features and conditions that provide effective presentation of educational services through information technology and the Internet. Recommendations for the digitalization of the educational process are outlined. The tasks concerning digitalization of educational process of future teachers of labor training and technologies are formulated; the model of transformations of the educational process of free economic education is offered. It leads to the creation of a new educational situation, the inclusion in the education system of new roles of the teacher, which changes the configuration of relations between its main participants. Digitization makes significant changes in the role of teacher and student in the learning process, which requires appropriate adaptation. Today, against the background of the COVID-19 pandemic, the transition to online education, the creation of a virtual educational environment create a need to change the management of the educational process. And if these changes do not occur, digitalization can have negative consequences. Scientists are widely discussing the problem of changes in the education system that occur under the influence of digitalization. Many papers on the benefits of digital technologies used in higher education Such benefits include students' wide access to educational information resources; opportunity to build individualized educational trajectories; transparency of educational organizations; optimization of interaction between teachers and students, between all participants in the educational process; formation of mobile structures for managing the educational process, etc. There are also skeptical assessments of the digitalization of education. The challenges facing the higher education system are discussed: increasing competition in the market of educational services due to the emergence of new providers, increasing student mobility, changing their demands for content, forms and technologies of learning, on the one hand, and the inability of free economic education to meet new requirements and implementing the full potential of digital technologies - on the other.