Reviewerly/exHarmony huggingface dataset:
Young people’s digital competences: does gender matter?

This research explores the intersections between gender and young people’s self-perceived digital competences. Previous research has identified differences between the self-perceived digital competences of girls and boys, but this paper further explores these differences comparing the ratings of ICT related curricular units with the self-perceived digital competences. A case study in one basic education school of Setúbal, Portugal, analyzed by gender the ratings to the ICT related curricular units, and the results of a digital competences self-assessment online questionnaire. The ICT related curricular units’ ratings showed that girls and boys have similar results, however the digital competences self-assessment online questionnaire identifies a lower self-perceived digital competence of girls, and decreasing as they get older. This understanding of how girls’ self-perceived digital competences vary with age is an important information to organize educational actions to reinforce girls’ self confidence in their digital competences and promote gender equality in technology-related professions.
Information Asymmetry

The chapter discusses “information asymmetry” as the critically important phenomenon for the very existence of communication. Information asymmetry is the reason the parties need to communicate to allow acquiring needed information and reducing the uncertainty in making decisions, But, from the other side extends the competences as the factor causing misinforming. The chapter presents misinforming hazards by adding the issue of asymmetric competence and double-sided asymmetry. Information asymmetry is a necessary condition for communication, but also is a factor that may cause misunderstanding.
Comparison of Different Subjective Test Methods

Different test methods have been standardized for assessing video quality of 2D videos, e.g., ITU-T Rec. P.910 (Recommendation ITU-T P.910: subjective video quality assessment methods for multimedia applications, 2008) and ITU-R Rec. BT.500-13 (Recommendation ITU-R BT.500-13: methodology for the subjective assessment of the quality of television pictures, 2012). Due to the lack of a standardized method to assess the visual quality for 360 $${ }^\circ $$ videos, studies have often used ITU-T Rec. P.910 (Recommendation ITU-T P.910: Subjective video quality assessment methods for multimedia applications, 2008) and ITU-R Rec. BT.500-13 (Recommendation ITU-R BT.500-13: methodology for the subjective assessment of the quality of television pictures, 2012) to evaluate the visual quality of 360 $${ }^\circ $$ videos. ITU-T P.919 (Subjective test methodologies for 360° video on head-mounted displays. Recommendation P.919, 2020) was the first standardized recommendation on subjective test methods for 360 $${ }^\circ $$ video – with contributions from the author. In this chapter, two different experiments are described and conducted in two different contexts in a lab setting. In the first experiment, the results of two different subjective test methods, M-ACR (Test 2) and DSIS (Test 3), were compared in two different contexts; namely, the M–ACR test was conducted in winter and the DSIS test in summer. In experiment 2, the results of three different subjective test methods, ACR (Test 4), M-ACR (Test 5), and DSIS (Test 6), were compared. These tests were conducted within a period of three weeks, thus having no difference in context in terms of seasons. Based on the reliability, test time, and general applicability of the procedure across different tests, a methodological framework for 360 $${ }^\circ $$ video quality assessment is presented in this chapter.
Kegiatan literasi untuk anak-anak di Dusun Brengosan Donoharjo Ngaglik Sleman Yogyakarta

Purpose − This activity aims to help elementary school-age children in Dusun Brengosan Donoharjo Sleman Yogyakarta who have problems with reading. For some children, online learning and periodic assignments made by the school are difficult to follow. The impact of this learning is that there are some children who do not master early reading and comprehension of reading content.&#x0D; Method − The method of this service activity is tutorial. Participants consisted of 7 children consisting of 2 children in grade 1 SD, 1 child in grade 3, 3 children in grade 4, and 1 child in grade 5. This activity is carried out every Sunday for 2 consecutive weeks . The first week is an assessment of all children's reading abilities (5-6 December 2021). Second week (December 12-13 2021), reading skill tutorial activities.&#x0D; Findings − The result of this activity is the increasing ability of 1st and 5th graders to distinguish similar letters. For grades 3 and 4, they understand the core concepts of the reading and can retell it in their own language. Children participating in literacy activities also showed high motivation in participating in activities from start to finish in all sessions. Parents and children expressed that they wanted this activity to continue. This activity is a supporting activity for the village program in the form of village literacy which is funded by a combination of funding sources from Tamanssiwa's Bachelor of Science University and Mitra Kas.
Boosting AutoML and XAI in Manufacturing: AI Model Generation Framework

Abstract The adoption of AI in manufacturing enables numerous benefits that can significantly impact productivity, efficiency, and decision-making processes. AI algorithms can optimize production schedules, inventory management, and supply chain operations by analyzing historical data and producing demand forecasts. In spite of these benefits, some challenges such as integration, lack of data infrastructure and expertise, and resistance to change need to be addressed for the industry to successfully adopt AI. To overcome these issues, we introduce the AI Model Generation framework (AMG), able to automatically generate AI models that adjust to the user’s needs. More precisely, the model development process involves the execution of a whole chain of sub-processes, including data loading, automated data pre-processing, cost computation, automatic model hyperparameter tuning, training, inference, explainability generation, standardization, and containerization. We expect our approach to aid non-expert users into more effectively producing machine and deep learning algorithms and hyperparameter settings that are appropriate to solve their problems without sacrificing privacy and relying on third-party services and infrastructure as few as possible.
Anomaly Detection in Manufacturing

Abstract This chapter provides an introduction to common methods of anomaly detection, which is an important aspect of quality control in manufacturing. We give an overview of widely used statistical methods for detecting anomalies based on k-means, decision trees, and Support Vector Machines. In addition, we examine the more recent deep learning technique of autoencoders. We conclude our chapter with a case study from the EU project knowlEdge, where an autoencoder was utilized in order to detect anomalies in a manufacturing process of fuel tanks. Throughout the chapter, we emphasize the importance of humans-in-the-loop and provide an example of how AI can be used to improve manufacturing processes.
Integrating Knowledge into Conversational Agents for Worker Upskilling

Abstract The labor market is a key part of an economy. Several existing online platforms allow the upload of resumes and the search for a job. One of their limitations, however, is that obtaining the best opportunity can be hard because certain jobs need some experiences, abilities, and features that an applicant might not know. The recent diffusion and employment of conversational agents definitely have proven to benefit this kind of issue. For example, ChatGPT has shown impressive outcomes in different domains and for a variety of tasks. It has weaknesses, although, related to the veracity of the responses it generates, which might deceive the user interacting with it. The usage of external domain knowledge is the direction we suggest in this chapter. Several lexical databases and taxonomies have already been collected and designed by different organizations. We illustrate a list of such resources and provide a solution that integrates conversational agents with relevant information extracted from one of such resources showing the benefits and the impact that our proposal can generate.
Object Detection for Human–Robot Interaction and Worker Assistance Systems

Abstract The primary goal of this research is to describe the scenarios, challenges, and complexities associated with object detection in industrial environments and to provide clues on how to tackle them. While object detection in production lines offers significant advantages, it also poses notable difficulties. This chapter delves into the common scenarios and specific challenges encountered in industrial object detection and proposes targeted solutions for various use cases. For example, synthetic data play a pivotal role in overcoming labeling challenges, particularly when it comes to small objects. By harnessing synthetic data, we can efficiently track and debug object detection results, ensuring faster identification and resolution of many data labeling issues. Synthetic data facilitate effective tracking and debugging of object detection results, streamlining the overall workflow. Furthermore, we explore the application of object detection in head-worn devices, utilizing the human point of view (POV) as a valuable perspective. This approach not only enhances human assistance systems but also enhances safety in specific use cases. Through this research endeavor, our aim is to contribute to the advancement of the whole process of object detection methods in complex industrial environments.
A Progressive Approach to Arabic Character Recognition Using a Modified Freeman Chain Code Algorithm

Arabic character identification presents a significant obstacle to the comprehension and analysis of Arabic text. This paper presents an improved technique that generates Freeman code from handwritten Arabic characters. This code provides the shortest code length without losing character information, accounting for all handwritten Arabic character variants. We tested this code using a set of Arabic characters in various formats to identify Arabic characters in order to take use of the code generated by our enhanced method. We also performed a comparison between our Freeman code and codes generated in other related research. In light of this, the code that we obtained correctly represents the Arabic letter in all of its variants, including the ones that the algorithms in previous publications did not consider. Consequently, our novel method based on Freeman coding represents a significant advancement in Arabic character recognition. Furthermore, our method provides a successful way of identifying and presenting Arabic characters.
The Effectiveness of Training Package based on Executive Functions of Delis-Kaplan on Reading skill of Dyslexic students

Background and Aim: Reading is considered as one of the first ways to acquire knowledge, and students with poor reading skills learn more during and after school. The present research aimed to evaluate effectiveness of training package based on executive functions of Delis-Kaplan on reading skill of dyslexic students. Method: This was quasi-experimental study with pre and post tests and following up. Statistical population was all male and female students in third grade in Tehran who were studying in 2018-19. Thirty dyslexic students were selected by multi- clustering random sampling, then according to inclusion and exclusion criteria, 15 subjects were selected for experimental group and 15 for control group. Experiment group received training package based on executive functions of Delis-Kaplan in 17 sessions each lasting for 60 minutes, but control group did not. The tools used in present research were Raven intelligence test and reading test of Kormi Noori and Moradi (2018). Data were analysed using covariance analysis by SPSS.22. Results: The results showed that training package based on executive functions of Delis-Kaplan has significant effect on reading skill in dyslexic children (p&lt;0/001). Conclusion: According to these results, it can be said that improving executive functions in early years of schooling may improve reading skills of dyslexic students
The Ecole francaise d'Extreme-Orient - Sarawak Museum Department Archaeological Project in Santubong

Archaeological research in Sarawak began just after the Second World War under the leadership of Tom Harrisson. As Curator of the Sarawak Museum since 1947, he began exploring the Sarawak River Delta, a 600 km area between Telaga Air in the northwest, Tanjung Sipang in the north, Tanjung Po in the northeast, Samarahan in the southeast and Kampung Makam in the southwest. It is the village of Santubong at the mouth of the Santubong River, one of the branches of the delta, that first caught Harrisson's attention because of observations and chance finds made there since the middle of the nineteenth century. Mention should be made of the famous Batu Gambar, an anthropomorphic sculpture in high relief on a rock at the Sungai Jaong site, rediscovered by a local in the 1880s, and near which was found a "Hindu" terracotta figurine, of carved stones reported at the beginning of the twentieth century on the neighbouring site of Bongkissam, "Indian character" pottery, as well as various objects in gold, Chinese coins and a few residues from ironworking (cf. especially Evans 1929).
I repeat therefore I am: The parasyntactic perspective

Abstract The text presents a theoretical platform and a case study of a new method for authorship attribution based on an author’s specific low-frequency lexicon. It will be shown that an author’s text is largely context-independent and is constructed by the author’s habit based on the regular repetition of certain topics or modes of expression. The author’s idiosyncratic way of choosing between synonymous linguistic devices in the text happens at a distance of several word forms or sentence units. This means that texts themselves are constructed using a much wider range of repetitions than expected and that the structure of the text above the level of intersentential linking is determined by a specific group of words (functional but above all content words) obligatorily used by the author in the formulation of the text. The newly introduced method can be used to attribute authorship by relying on the specific linguistic imprint of the author in the text (in this context, we talk about parasyntactic linguistic level). The method is compared with a function-word-based method.
Software Maintainability and Refactorings Prediction Based on Technical Debt Issues

Software maintainability is a crucial factor impacting cost, time and resource allocation for software development. Code refactorings greatly enhance code quality, readability, understandability and extensibility. Hence, accurate prediction methods for both maintainability and refactorings are vital for long-term project sustainability and success, offering substantial benefits to the software community as a whole. This article focuses on prediction of software maintainability and the number of needed code refactorings using technical debt data. Two approaches were explored, one compressing technical debt issues per software component and employing machine learning algorithms such as ExtraTrees, Random Forest, Decision Trees, which all obtained a high accuracy and performance. The second approach retained multiple debt issue entries and utilized a Recurrent Neural Network, although less effectively. In addition to the prediction of the requisite number of code refactorings and software maintainability for individual software components, a comprehensive analysis of technical debt issues was conducted before and after the refactoring process. The outcomes of this study contribute to the advancement of a dependable prediction system for maintainability and refactorings, presenting potential advantages to the software community in effectively managing maintenance resources. Of all the employed models, the ExtraTrees model yielded the most optimal predictive outcomes. To the best of our knowledge no other approaches of using ML techniques for this problem have been reported in the literarture. Keywords and phrases: Software Quality, Sonarqube, Refactoring, Code Smells.
Position of State-Funded Students in Kharkiv University in the 19th and early 20th centuries

The article highlights the peculiarities of professional training and life of Kharkiv University students who had the right to study at state expense. In the conditions of the dominance of elitist education, accessible to a limited circle of young people due to its high cost and social and religious discrimination, in the first half of the 19th century. The institution of state-funded students allowed talented young people to get a higher education and realize themselves in the scientific or bureaucratic field. In the future, a number of scholarships from state institutions and private individuals were introduced to financially support talented student youth. The use of general scientific principles of historicism and objectivity and the application of analytical, descriptive, comparative-historical methods made it possible to comprehensively study the conditions of study and the level of training of students who studied at public expense at Kharkiv University during the 19th and early 20th centuries. The research is conducted on the basis of a wide source historical base (legislative acts of the Russian Empire, internal documentation of the university and memoirs of graduates of the institution). The paper attempts to analyze and systematize the source base on the issue of providing benefits to students of Kharkiv University.It has been proven that in order to attract talented young people to study at the university, the institution of state-financed students who were fully supported by the state is being introduced. However, the introduction of strict rules for privileged students, the administration’s complete control over their lives did not contribute to the popularization of the status of state-funded student among young people. From the second half of the 19th century the institute of state-funded students was liquidated, instead the tradition of awarding scholarships was introduced. It should be emphasized that thanks to the efforts of patrons, the number of monetary awards constantly increased and was one of the largest among the universities of the Russian Empire. Strict requirements for candidates for monetary rewards contributed to improving the level of self-training of students.
A Comparison of Genetic Algorithms in Optimizing Controllers for Inverted Pendulum

In our study, we compared classical genetic algorithm (GA) and non-dominated sorting GA (NSGA) II to optimize LQR and sliding mode control (SMC) for an inverted pendulum. We aimed to identify the algorithm that best improves stability and peak performance. Our results clarified each algorithm's unique strengths. The provement is shown in Matlab simulations.
Application of Fuzzy-ANFIS Controller for Ball on Wheel System

The ball-on-wheel (BoW) is a nonlinear single input-multi output (SIMO) system consisting of a ball located on a wheel. The system's challenge is to balance ball at the highest point on the wheel. In this paper, we propose a method of applying ANFIS toolbox in imitating a successful controller (in this case, it is PD controller). This process creates a similar fuzzy controller which controls well this system. Therefore, through this research, ANFIS toolbox shows the ability in imitating an expert‘s control law through collecting data of operations.
Ensemble Learning Approach for Effective Software Development Effort Estimation with Future Ranking

To provide a client with a high-quality product, software development requires a significant amount of time and effort. Accurate estimates and on-time delivery are requirements for the software industry. The proper effort, resources, time, and schedule needed to complete a software project on a tight budget are estimated by software development effort estimation. To achieve high levels of accuracy and effectiveness while using fewer resources, project managers are improving their use of a model created to evaluate software development efforts properly as a decision-support system. As a result, this paper proposed that a novel model capable of determining precise accuracy of global and large-scale software products be developed with practical efforts. The primary goal of this paper is to develop and apply a practical ensemble approach for predicting software development effort. There are two parts to this study: the first phase uses machine learning models to extract the most useful features from previous studies. The development effort is calculated in the second phase using an advanced ensemble method based on the components of the first phase. The performance of the developed model outperformed the existing models after a controlled experiment was conducted to develop an ensemble model, evaluate it, and tune its parameters.
Radar Tasikmalaya News Portal's Error Analysis in the Indonesian Language from a Linguistic Category Point of View

There are still many online news portals that make writing errors, not only in terms of spelling, but also in terms of morphology, syntax and semantics. The goal of this language mistake analysis is to analyze and repair phonological, morphological, syntactic, and semantic faults found on instructional pages of the Radar Tasikmalaya news site. The researcher employed a descriptive analytic method. The research methods employed in this study were observation, interviews, and literature studies, which involved reviewing all of the books, articles, notes, and reports that had anything to do with the issue being addressed. By performing numerous steps in the study process, including: (1) gathering data, (2) describing the data, (3) evaluating the data, and (4) drawing conclusions. The findings of a language mistake study for the Radar Tasikmalaya news portal's edition can be concluded that there are forms of language errors in the fields of phonology, morphology, syntax, and semantics. In linguistic-morphological category errors there are errors in affixation. Syntactic errors consist of errors in sentence construction. There are also semantic errors consisting of errors in the meaning of sentences that can make the reader misinterpret the sentence. Then there are errors in the use of spelling or phonology, these spelling errors consist of writing errors in the use of punctuation marks, especially in writing academic degrees, using standard words, writing foreign terms, and writing capital letters.