Reviewerly/exHarmony huggingface dataset:
Data Bias Detection in Machine Learning Using Various Statistical Measures

The study discusses numerous statistical techniques for bias identification. The techniques are used with binary and multinomial dafigta. Artificial intelligence (AI) is a broad term referring to machines or computers that mimic human intelligence. Machine learning (ML), a subdomain of modern AI, creates rules based on training data. The Bias detection of data and model are essential in today’s scenarios. The mitigated data will give better prediction results. Good predictions help organizations to take better decisions.
Towards a Cybersecurity Culture-Behaviour Framework: A Rapid Evidence Review

A strong organisational cybersecurity culture (CSC) is critical to the success of any cybersecurity effort, and understanding and measuring CSC is essential if it is to succeed. To facilitate the framing and measurement of CSC we conducted a rapid evidence assessment (REA) to synthesise relevant studies on CSC. The systematic search identified 1,768 records. 52 studies were eligible for the final synthesis. Content analysis of the CSC definitions in the eligible studies highlighted that CSC should not be viewed solely as a technical problem but as a management issue too; CSC requires top management involvement and role modelling, with full organisational support for the desired employee behaviours. We identify both theoretically and empirically derived models of CSC in the REA, along with a range of methods to develop and test these models. Integrative analysis of these models provides detailed information about CSC dimensions, including employee attitudes towards CS; compliance with policies; the role of security education, training and awareness; monitoring of behaviour and top management commitment. The evidence indicates that CSC should be understood both in the context of the wider organisational culture as well as in the shared employee understanding of CS that leads to behaviour. Based on the findings of this review, we propose a novel integrated framework of CSC, consisting of cultural values; the culture-to-behaviour link and behaviour itself. We also make measurement recommendations based on this CSC framework, ranging from simple, broad-brush tools through to suggestions for multi-dimensional measures, which can be applied in a variety of sectors and organisations.
Multiscale Feature Fusion Network for Monocular Complex Hand Pose Estimation

Hand pose estimation based on a single RGB image has low accuracy due to the complexity of the pose, local self-similarity of finger features, and occlusion. A multiscale feature fusion network (MS-FF) for monocular vision gesture pose estimation is proposed to address this problem. The network can take full advantage of different channel information to enhance important gesture information, and it can simultaneously extract features from feature maps of different resolutions to obtain as much detailed feature information and deep semantic information as possible. The feature maps are merged to obtain the hand pose results. The InterHand2.6M dataset and Rendered Handpose Dataset (RHD) are used to train the MS-FF. Compared with the other methods (which can estimate interacting hand poses from a single RGB image), the MS-FF obtains the smallest average error of hand joints on RHD, verifying its effectiveness.
Introduction

The introductory chapter defines the motivation for writing this book. It introduces the general topic of androids as understood in this book, and places it in the context of AI research.
Research on Media Presentation and Public Reaction to the First Health Digital Assistant in Croatia

This research paper investigates the perception, acceptance, and media presentation of the digital assistant Andrija in the healthcare sector during the COVID-19 pandemic. The research used combined methods that include analysis of the media presentation of the Andrija project and the public's reaction on Facebook, collection of public announcements on the Facebook social network, and their quantitative and qualitative analysis. The research sample consisted of 82 posts on Facebook that corresponded to the keywords "Andrija, digital assistant". The research results show that Andrija digital assistant played a key role in providing basic information about the COVID-19 pandemic and supporting the public in making informed decisions. The analysis of the media presentation of the Andrija project on Facebook revealed a diversity in the size of the posts, with an emphasis on image/video material and the presence of links to official websites. Also, Andrija chatbot was generally well received, with a high number of "Like" reactions and emotional connection expressed through "Love" reactions on analyzed Facebook posts. However, there are variations in user perception. Examination of the correlation between the size of the post (number of words) and reactions on Facebook posts did not show a statistically significant correlation between the size of the post and the total number of quick reactions, but a statistically significant positive correlation was found between the size of the post and the number of "Like" reactions.
Leveraging Latent Natural Language Processing Techniques for User Story Management in Agile Software Development

User story management is a critical aspect of agile software development, as it involves understanding and prioritizing the needs of stakeholders, and translating them into actionable tasks for development teams. Furthermore, the identification of new activities within products is crucial for enhancing software quality assurance, and user story management is a crucial component of agile software development and software testing. Reusing manually written test steps would be a waste of time and effort for the testers because requirements in agile software development are continually changing and eventually becoming out-dated. Therefore, developers need to implement the necessary functions and write test steps for user stories to determine the desired behaviour or desired result of the program. In an agile world, the user story is the link between the customer and the development team, as well as the main pillar on which the development team relies to understand the product requirements. Therefore, developers need to implement the necessary functions and write test steps for user stories to determine the desired behaviour or desired result of the program. Since agile testing can detect defects early in the software life cycle and deliver a high-quality product, we propose our approach to generating test cases using natural language processing to analyse the user story. Therefore, Neural Language Processing (NLP) techniques help the development team to obtain clear data and achieve customer satisfaction.
Features of Creating Parallel Programs for the Parallel Dataflow Computing System "Buran"

The use of modern multi-core and multi-processor computer systems for actual tasks is not effective enough, even taking into account the use of parallel programming technologies. The solution to the problem of efficient loading of computing resources can be the transition to computing models and architectures that are inherently parallel. One of such architectures is the Parallel Dataflow Computing System (PDCS) "Buran", which implements a dataflow computing model with a dynamically formed context. A feature of the dataflow computing model is the activation of computations by data readiness, which affects both the architecture of the computing system and the creation of programs for such systems. Differences between imperative and dataflow programming paradigms are also reflected in the route of creating a program, especially its parallel implementation. The route of creating a dataflow parallel program differs markedly from the traditional one. Already at the first stage, a parallel algorithm is created and implemented (including the algorithm for generating initial data). Next, this algorithm is debugged when it is executed on an emulator or model of the system with one computing core. After that, the selection and configuration of function of computation distribution is performed, the program is executed (without changing its code) on the emulator or model of the system with several computing cores, and, finally, the program is debugged in multi-core mode. These stages of the route differ from similar stages of the traditional route, both in form and in essence. Unlike traditional parallel, and even more so sequential programs, it can be said that a dataflow program in equal parts consists of a program code that implements a task, an algorithm for generating initial data, and a function of computation distribution. This thesis is demonstrated by the example of solving the problem of finding sum of array elements, where the difference between the implementations is in the algorithm for generating initial data, which radically affects the nature of the dataflow program passing. Careful attention to each of the parts of the dataflow program is the key to the correct and efficient solution of problems on the PDCS, which provides support to the programmer at the hardware level.
Research on the Approach of Integrating “Ke-Cheng Si-Zheng” Elements into Physical Education under the “Double Reduction” Policy

This article aims to explore the organic integration of physical education with Ke-Cheng Si-Zheng elements within the curriculum, considering the backdrop of the “double reduction” policy. Through a review of relevant literature and empirical research, we have identified deficiencies in both the inclusion of Ke-Cheng Si-Zheng elements and the oversimplification of physical education's role in current curriculum design and implementation. We propose strategies to enhance curriculum design and textbook development, improve teacher training and professional development, foster interdisciplinary collaboration and resource sharing, organize distinctive activities and practical projects, and innovate the application of educational technology. These efforts aim to facilitate the seamless integration of physical education with Ke-Cheng Si-Zheng elements within the curriculum. Ultimately, this research provides theoretical underpinnings and practical guidance for physical education instruction in schools.
Reasonable Compensation for Creative Labor: International Practices and Precedents of Audiovisual Author’s Unwaivable Right to Remuneration

For copyright to achieve its original purpose, creators should be entitled to fruits of successful exploitation of their work after they license or transfer their rights. Due to imbalance of bargaining power, creators often sign away their rights to compensation. To respond that, we need to think about legislating an unwaivable right. Its operation resembles the fee collecting systems already set up for television writers and actors in Korea and for music writers and performers around the world, which originate from historical reasons, collective power, or the statutory compensation for performing music recordings. The last example is enshrined by Rome Convention and WPPT, and its modus operandi can be easily applied to audiovisual recordings. When the 2016 Beijing treaty does exactly that for audiovisual performers (i.e., actors and actresses) and where digital technology makes collection of fees for various ways of communicating the audiovisual works to the public, the time is ripe to seriously consider the audiovisual authors’ unwaivable right to remuneration extending beyond performers and inclusive of directors and script writers. In doing so, it will be desirable to take the form of compulsory licensing for copyright limitation so that the right to remuneration exists even when the creators have not made licensing or transfer. Collective management societies’ collecting activities may be more efficient than filing lawsuits for copyright infringement.
A study on the development of mathematical competency test using manipulatives

As most countries place emphasis on competency-based education in mathematics to prepare for the future, it's important to create reliable testing instruments. The purpose of this study is to develop and validate a mathematical competency assessment tool that incorporates teaching aids. Initially, 16 stages of testing tools from K-1 to B-IV were developed for the validation process. Following this, a total of 6,430 lower elementary school students, including kindergarteners, were administered these assessment tools, and the completed results of 3,234 were analyzed. This study underscores that the developed assessment tools have proven to be valid and reliable in accurately reflecting students' mathematical competencies. Additionally, these tools, using teaching aids, were effective in engaging young students in the evaluation process and assessing their mathematical competencies accurately. The study concludes with a proposal for future research on the development of high-quality questions, teacher training, and the incorporation of more diverse teaching aids, including virtual manipulatives, for evaluating mathematical competencies in kindergarten and elementary school students.
Development of mathematics teaching and learning materials using robots to improve computational thinking

This study aimed to develop teaching and learning materials that can improve computational thinking in the areas of high school functions and analysis by using robots. Through a literature review, we analyzed research on computational thinking and examined how computer programming and coding education are being conducted in domestic and international mathematics curricula. We then restructured the Carnegie Mellon University DBL Unit to propose a DBL Unit model that utilizes robots, and we developed mathematics teaching materials using LEGO Mindstorms EV3 for units in the areas of functions and analysis. Subsequently, based on the Delphi survey results, we revised the developed materials and provided recommendations for enhancing computational thinking in mathematics classes.
Correlation between Grammatical and Pragmatic Competences among Indonesian University EFL Learners

Language competence not only refers to the underlying knowledge of the linguistic aspects of the language system under study, such as grammar and lexis, but also an understanding of the extra-linguistic features of a given communicative scenario, all of which contribute to meaning and the interpretation of meaning, This study aims to: (1) to determine whether there is a correlation between EFL Indonesian university students’ grammatical competence and their pragmatic competence, and (2) to investigate the influence of students’ grammatical competence towards their pragmatic competence. The data collected are from year 2 English students by using grammatical and pragmatic tests for students to answer. Their answers were analyzed quantitatively to obtain the mean score and further will be compared. The results show that: 1) students perform low on both aspects (m1=8.78, and m2=10.46, 2) there is a moderate positive correlation between the two sections (r=.54, p=0.01), and 3) students’ grammatical knowledge contributes on their pragmatic knowledge on medium level (t(65)=-.36, p=0.01). The average level of achievement that students could attain on grammar shows that it is still a challenging aspect in FL learning despite they have received 4 compulsory grammar subjects. This challenge should be taken into concern as the result of this study also shows that grammatical competence could affect learners’ initial competence on pragmatic as week. Therefore, there is a need of improvement on EFL teaching methods especially for grammatical subjects due to very low achievement on this central skill which will contribute to the other skills.
Text Messaging in English and Arabic with Reference to Translation

In the twenty-first century, many people now live their lives through text messaging. In fact, you can witness people using their cell phones to send character-based messages to their friends, classmates, family members, and coworkers in malls, schools, and pretty much anywhere else. The popularity of this method of communication has increased particularly among young people. One benefit is that technology enables people to speak with others virtually anywhere. Second, it enables individuals to speak softly, which is useful in noisy places like bars, where it would be challenging to have a productive conversation over the phone, or when extraneous communication needs to be done quietly, such as in a school. Thirdly, it combines some of the advantages of phone and email communication by allowing them to communicate both synchronously (i.e., two-way communication occurs concurrently) and asynchronously (i.e., two-way communication is delayed). The usage of acronyms, abbreviations, and other shorthand notations has become commonplace in this technology's creation of a new language form. The focus of this research is on these qualities specifically and how they are used. The aim of this study was to analyze not only how frequently but also how these symbolic expressions are used in relation to the linguistic functions that they signal, which was followed by a number of discoveries.
Estimated Posture for Human Elbow Flexion in Acoustic Environments

The present study proposes a novel approach to address the challenge of identifying smoking and phone usage behaviours among individuals amidst the intricate surroundings of construction sites. Specifically, the method involves the recognition of elbow flexor behaviours through posture estimation. The localization and detection of key points pertaining to the human upper body have been achieved through the application of AlphaPose. Subsequently, the present study introduces the HEFBD model, which is a mathematical framework that discriminates human elbow flexion behaviour. The model is constructed using human key points and is designed to identify the area that is relevant for recognising tiny objects while mitigating the impact on the complicated background. A method for image reconstruction with super-resolution is employed as a pre-processing technique for images that exhibit blurring. Furthermore, the performance of You Only Look Once (YOLO) has been enhanced through the incorporation of a tiny object identification layer and the integration of a convolutional inhibitory attention model, thereby improving its detection capabilities. The method has demonstrated an improvement in detection precision of 6.7 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> and a reduction in false identification rates due to complex backgrounds of 12%. These outcomes outperform existing detect approaches and meet the requirements for immediate results.
Ultrasound Image Denoising Using Cascaded Median Filter and Autoencoder

Ultrasound Images are vital to accurately diagnose various ailments in the medical field. Usually., the ultrasound images contain many noises one such is salt and pepper noise. This has a considerable negative effect on the medical diagnosis. In order to remove the salt and pepper noise., this study proposes a cascaded model where we use high efficiency filters such as median filter and then combine a neural network such as DnCNN or Autoencoder to effectively remove noise while retaining important feature information. Experimental outputs show that our denoising method has improved results.
Modular Distance Learning in the New Normal: Challenges on its Implementation

This basic research was conducted to determine the challenges of teachers in the implementation of modular distance learning in the new normal of the public elementary and secondary schools in the District of Gitagum, Division of Misamis Oriental. Specifically, it sought to: a) describe the characteristics of the respondents; b) determine the challenges encountered by the teachers in terms of accessibility, availability of resources, support to learners, teachers’ competence and teaching strategies, assessment, and health and safety measures; c) determine the significant relationship between the respondents’ challenges and their characteristics; and d) come up with an intervention plan based on the results of the study. The respondents of the study were the one hundred five (144) public school teachers in the District of Gitagum, Division of Misamis Oriental. A researcher-made survey questionnaire was employed to obtain specific information about the study. The data were analyzed using descriptive statistics such as frequency counting of data, percentage, mean and standard deviation. Pearson Product Moment of Correlation was employed to test the significant relationship between the respondent’s challenges and their characteristics. An intervention plan was designed to help teachers in finding solutions to the challenges they are facing in the implementation of modular distance learning. The teachers’ challenges were low in the implementation of modular distance learning. It suggests that teachers faced few challenges or that the challenges they encountered were of low intensity. In other words, it implies that teachers found it relatively manageable to implement modular distance learning, and the difficulties they encountered were not severe. Teachers’ challenges were significant to sex, position, teaching experience and attitudes towards modular distance learning in the new normal. It is recommended that teachers seek support from stakeholders and the local government to acquire funds for better implementation.
The Analysis of Politeness Strategies and Kinship Relationship: A Study Case of Wawonii Educational Background Compared to American

This research aims (1) to analyze the types of politeness strategies used by Wawonii speakers compared to American in daily conversations, and (2) to explore the educational background defined politeness strategies of Wawoniiese compared to American. The research used the quantitative research method. Wawoniiese data were collected from 32 respondents in North East Wawonii through questionnaire, observation, interview, and recorded dialogue form of speech. American data were taken from transcribed conversations of selected movies. The research result found that Wawoniiese and American speakers used four of the Politeness Strategies by Brown and Levinson. They were Bald-on-record, Positive Politeness, Negative Politeness, and Off-record. Furthermore, this research also found that the politeness systems of young and older people are almost similar, for instance, both systems showed 93,75% of speakers used deferent speech variety when talking to Parents-in-law. Meanwhile, when adding the educational background, the result showed more variations in politeness systems. Despite having age differences the older and younger family members can have conversations in mixed and casual varieties due to the influence of the educational background of speakers. For instance, the politeness systems by well-educated showed 37,5% of speakers used mixed speech variety and 56,25% of speakers used casual speech variety when talking to older cousins. Therefore, in Wawonii notably in North East Wawonii the educational background of speakers is the factor that significantly defines the choice of people's utterances compared to the variable of age. Hence, this research concluded that educational background influenced the politeness strategies of Wawonii speakers but not of American.