Reviewerly/exHarmony huggingface dataset:
Motivational Case Study Videos With R Analyses of the Data

Twenty motivational videos that focus on applied statistics are available on the University of Otago website. These are accompanied by data and lessons that are targeted at students in schools and universities that use GenStat software. The videos and lessons cover a range of techniques and have been popular with over 100,000 page visits since 2011. We outline transitioning the lessons to R software. R is freely available and widely used, including in the statistics curriculum at the University of Otago. The updated lessons are written using the Quarto package and are available online. Relative to static documents, no downloads are required, and the lessons offer new possibilities for interaction between the students and code.
UEFI virtual machine firmware hardening through snapshots and attack surface reduction

The Unified Extensible Firmware Interface (UEFI) is a standardised interface between the firmware and the operating system used in all x86-based platforms over the past ten years. A side effect of the transition from conventional BIOS implementations to more complex and flexible implementations based on the UEFI was that it became easier for the malware to target BIOS in a widespread fashion, as these BIOS implementations are based on a common specification. This paper introduces Amaranth project - a solution to some of the contemporary security issues related to UEFI firmware. In this work we focused our attention on virtual machines as it allowed us to simplify the development of secure UEFI firmware. Security hardening of our firmware is achieved through several techniques, the most important of which are an operating system integrity checking mechanism (through snapshots) and overall firmware size reduction.
ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation

There has been a recent surge in methods that aim to decompose and segment scenes into multiple objects in an unsupervised manner, i.e., unsupervised multi-object segmentation. Performing such a task is a long-standing goal of computer vision, offering to unlock object-level reasoning without requiring dense annotations to train segmentation models. Despite significant progress, current models are developed and trained on visually simple scenes depicting mono-colored objects on plain backgrounds. The natural world, however, is visually complex with confounding aspects such as diverse textures and complicated lighting effects. In this study, we present a new benchmark called ClevrTex, designed as the next challenge to compare, evaluate and analyze algorithms. ClevrTex features synthetic scenes with diverse shapes, textures and photo-mapped materials, created using physically based rendering techniques. It includes 50k examples depicting 3-10 objects arranged on a background, created using a catalog of 60 materials, and a further test set featuring 10k images created using 25 different materials. We benchmark a large set of recent unsupervised multi-object segmentation models on ClevrTex and find all state-of-the-art approaches fail to learn good representations in the textured setting, despite impressive performance on simpler data. We also create variants of the ClevrTex dataset, controlling for different aspects of scene complexity, and probe current approaches for individual shortcomings. Dataset and code are available at https://www.robots.ox.ac.uk/~vgg/research/clevrtex.
A Study of the Quality of Wikidata

Wikidata has been increasingly adopted by many communities for a wide variety of applications, which demand high-quality knowledge to deliver successful results. In this paper, we develop a framework to detect and analyze low-quality statements in Wikidata by shedding light on the current practices exercised by the community. We explore three indicators of data quality in Wikidata, based on: 1) community consensus on the currently recorded knowledge, assuming that statements that have been removed and not added back are implicitly agreed to be of low quality; 2) statements that have been deprecated; and 3) constraint violations in the data. We combine these indicators to detect low-quality statements, revealing challenges with duplicate entities, missing triples, violated type rules, and taxonomic distinctions. Our findings complement ongoing efforts by the Wikidata community to improve data quality, aiming to make it easier for users and editors to find and correct mistakes.
Application of Three Convolutional Neural Network Algorithms for Occluded Face Identification and Recognition for System Security

Deep Learning techniques in computer vision have become indispensable elements in biometric systems, especially face recognition. Facial recognition can be reliably used as an identification and authentication tool for premises or network access security. The masks wearing, which is one of the problems of concealment, are nowadays part of our habits for preventing COVID-19 disease, which leads to an obstruction of facial recognition. Occulted face recognition is one of the most challenging problems biometrics deals with. This paper presents convolution neural network algorithms for occluded face recognition. Our study presents a robust method using algorithms such as ResNet-50, VGG-19, and DenseNet-201 to contribute to occluded face recognition. Various parameters are used for this experiment, such as the cross-entropy used as a loss function and optimization algorithms adapted to deep learning. These include the SGD, Adam, and RMSProp optimizers. The convolution neural network algorithms were evaluated on the AR database. This experiment gave results that ranged from 94.81 to 99.81% for SGD, from 0 to 96.92 for Adam, and finally from 0 to 96.92 for RMSProp. DenseNet-201 algorithm using the SGD optimizer obtained the best score with 99.81%, and all the performance metrics used such as accuracy, MSE, F-score, recall, and MCC were used to confirm this good performance.
METHODICAL ASPECT OF DEVELOPMENT OF FUTURE PSYCHOLOGISTS’ CAREER ORIENTATIONS IN THE CONTEXT OF THEIR PROFESSIONALIZATION

The article is devoted to the problem of purposeful development of future psychologists’ career orientations in the context of their professional self-determination and self-realization. The requirements of modern society for specialists in the field of socio-economic professions and the role of forming career orientations taking into account the specifics of professional work in this field are considered. The concept of a professional career, its structure and the place of career orientations in it are analyzed. The article also presents the results of an empirical study of the motivation to achieve success among student youth as one of the essential prerequisites for the development of career orientations of future specialists. The results of the study of the specificity of different types of psychology students’ career orientations according to the method of E. Shein, taking into account the peculiarities of their motivation to achieve success, are considered. Special attention is paid to researching the reasons for young people of choosing a particular type of career and possible difficulties and obstacles along the way. Methodical means of developing the components of career orientations of student youth are outlined through increasing the motivation to achieve success, primarily during the organization of the educational process in higher education. The possibilities of applying the system of both traditional and innovative methodical means of developing student youth's abilities to self-knowledge and awareness of the specifics of the future profession and, as a result, to the design of a further professional career and its successful implementation are analyzed.
PROFESSIONAL SELF-IDENTITY OF FUTURE PSYCHOLOGISTS IN INSTITUTIONS OF HIGHER EDUCATION

The article analyzes theoretical and empirical approaches to the study of psychological prerequisites for the development of professional self-identity. The peculiarities of the future psychologists motivational sphere development as a key component of professional self-identity, the psychological and pedagogical conditions of its formation are theoretically investigated; principles of studying self-identity among psychologists are presented.&#x0D; Methodological principles and diagnostic methods of researching the peculiarities of the professional self-identity of future psychologists and its factors are methodologically substantiated. The results of an empirical study, which characterize the peculiarities of the professional self-identity of psychology students at various educational stages of professional mastery, are analyzed.
MOTIVATIONAL READINESS OF CRIMINAL INVESTIGATION DEPARTMENT OFFICERS TO PROFESSIONAL ACTIVITY

The article presents the results of theoretical and experimental research of psychological peculiarities of the motivational readiness of criminal investigation department officers to professional activity. This problem was actualized by the fact that in the current conditions in many regions of the country the workload on the officers of the internal affairs bodies, in particular, the employees of the criminal investigation departments, has increased significantly. &#x0D; As a result of the theoretical analysis, it was found that the complexity of the activity of criminal investigation department officers dictates the high requirements for the professional training of each officer. Investigative activity requires an officer of internal affairs bodies to have appropriate professional training and a clear understanding of the main values of the profession. The motivation of professional activity is an important component in the development of a young specialist. The formation of motivational readiness is possible under the condition of a certain social guarantee to the officer from the system of internal affairs bodies and the activation of the process of theory and practice combining during the period of mastering the profession. &#x0D; The data of the experimental research of the motivational readiness of criminal investigation department officers to professional activity proved the preference of extreme types of activity among professional inclinations. These are the professions related to security and investigative activities, since different situations of an official nature are possible in the activity of law enforcement officers. Inclinations to research activity are also significant. In the hierarchy of motives for choosing a profession by officers of the criminal investigation sector of the Ministry of Internal Affairs, those motives that are significant for the implementation of the chosen professional activity, namely internal individually significant motives and external positive motives, dominate. This proves that law enforcement officers are focused on the profession and strive to work effectively on mastering it in the future, as they consider the chosen profession to be their vocation and want to reveal creatively and express themselves in it. &#x0D; The attitude of the subjects to labor activity is positive in general. In addition, it was possible to prove that subjects with developed internal individually significant motives for choosing a profession have a higher level of readiness to master the profession of an investigator.
COMPONENT-STRUCTURAL ANALYSIS OF EMOTIONAL STABILITY IN THE MUSIC-PERFORMING ACTIVITIES OF CHILDREN'S MUSIC SCHOOL STUDENTS

The article reveals the problem of the formation of emotional stability in students of a children's music school. In this aspect, the author carries out a component-structural analysis of the studied formation and singles out the following components: motivational-volitional; information and activity; emotional and personal. It has been proven that the motivational and volitional component has a stimulating effect on the effectiveness of the process of improving students' executive and mental activity; informational and activity ensures that students accumulate the necessary knowledge, skills and abilities, the ability to reproduce a musical image in stage conditions, which is necessary for the formation of emotional stability in musical and interpretive activities; emotional and personal – reveals in students the external and internal factors of the studied phenomenon, the ability to self-evaluate and reflect on musical-interpretive activities, the ability to correct one's own mental and emotional state on stage, focused on self-development and further professional growth. The methodological basis of the research is dialectical and systemic methodologies used in the field of pedagogical research. General scientific and logical methods of analysis, synthesis, induction and deduction, historical and comparative research of the problem are used. The subject of further research in this direction may be the study of the conditions for the formation and development of the stress and adaptation potential of emotional stability. We assume the presence of close correlations between the level of emotional stability and the effectiveness of overcoming emotional disruptions, stability in this case will indicate the severity of stress and adaptive capabilities of the individual.
Emotion research on education public opinion based on text analysis and deep learning

Education public opinion information management is an important research focus in the field of Education Data Mining (EDM). In this paper, we classify the education data information based on the traditional Flat-OCC model. From the cognitive psychology perspective, we identify up to 12 kinds of emotions, including sadness and happiness. In addition, the EMO-CBOW model is also proposed in this paper to further identify emotion by using various emoticons in educational data sets. The empirical result shows that (1) the proposed Flat-OCC model can classify and identify the emotion of education public opinion data well; and (2) for the recognition of educational emotion classification, the categorization accuracy of the Flat-OCC+EMO-CBOW model is significantly higher than that of a single Flat-OCC model, which reveals that the emotional-pack-based model we propose can enhance our benchmark model.
Multivariate Time Series Dataset of Milling 16MnCr5 for Anomaly Detection

Machine learning methods have widely been applied to detect anomalies in machine and cutting tool behavior during lathe or milling. However, detecting anomalies in the workpiece itself did not get the same attention by researchers. That is why in this article, the authors present a pub-licly available multivariate time series dataset which was recorded during milling of 16MnCr5. Due to artificially introduced, though realistic anomalies in the workpiece the dataset can be ap-plied for anomaly detection. By using a convolutional autoencoder as a first model good results in detecting the location of the anomalies in the workpiece were achieved. Furthermore, milling tools with two different diameters where used which led to a dataset eligible for transfer learn-ing. The objective of this article is to provide researchers with a real-world time series dataset of the milling process which is suitable for modern machine learning research topics like anomaly detection and transfer learning.
Hateful Counterspeech

Abstract Faced with hate speech, oppressed groups can use their own speech to respond to their verbal oppressors. This “counterspeech,” however, sometimes itself takes on a hateful form. This paper explores the moral standing of such “hateful counterspeech.” Is there a fundamental moral asymmetry between hateful counterspeech, and the hateful utterances of dominant or oppressive groups? Or are claims that such an asymmetry exists indefensible? I argue for an intermediate position. There is a key moral asymmetry between these two forms of speech. But, this asymmetry notwithstanding, hateful counterspeech is capable of enacting serious harms—and so, contrary to what many legal theorists have argued, it is in principle an appropriate object of legal regulation. I begin by considering the central argument for thinking that hateful counterspeech is not seriously troubling. This argument holds that oppressed groups lack authority—and, by extension, “speaker power.” Yet this argument, I suggest, sits in tension with the fact that low-status members of dominant groups can, through their utterances, seriously harm members of oppressed groups. Philosophers of language have developed sophisticated arguments to explain this last phenomenon: they have argued that speaker power is relativised to particular jurisdictions; that it can be acquired dynamically in local settings; and that it is socially dispersed. I argue that, in light of these arguments, it appears that hateful counterspeech, too, can generate serious harms. Nevertheless, I show that this conclusion is compatible with recognising a crucial moral asymmetry between hateful counterspeech and the hate speech of oppressors.
Accurate: Penunjang di Era Digitalisasi untuk Meningkatkan Kompetensi dan Profesionalisme Guru dan Murid SMK

Abstract - Covid-19 pandemic has brought many changes for education, working life and so on. Digitalization is increasingly felt and forced to change from being face-to-face to online, so inevitably world moves faster to accelerate the use of technology. Technology development also applied in industry, including in terms of accounting records. The importance of debriefing for teachers and students of VHS, especially accounting vocational, related to using Accurate accounting software which has been widely used. This training improves self-competence and competitiveness in the face of digitalization. Therefore, Pusat Penelitian dan Pengabdian Masyarakat TSM in collaboration with TSM lecturers help to provide training for teachers and students to recognize and able to operate one of accounting software that has been widely used, especially by SME industry in Indonesia, namely Accurate. The purpose of this training is to provide briefing to teachers and students in understanding and operating various features in Accurate related to accounting transactions which are expected to improve skills in using this software. The training method includes Accurate introduction session, simulation, journal and financial statements discussion. Targets and outcomes to be achieved from this training are increased the understanding and skills of teachers and students in operating Accurate so the students could meet the requirements of world of work in terms of the use of technology.
A Review on the Weakness of UAM Corpus Tool

Due to the scarcity of evaluation on UAM in previous studies and lack of knowledge of UAM corpus tool for beginners, this paper carries out a comprehensive investigation and makes a review on its merits and demerits, especially demerits. A lot of studies related to UAM from various perspectives within linguistics, mainly describe it as a research instrument rather than a research object. In the meantime, an evaluation standard has been employed in the assessment of UAM corpus tool in this study. According to these principles and other scholars’ analysis on UAM, its main weakness contains limited access, restricted applied domain, not sufficiently accurate automatic and manual annotation, among others. In the longer term, this research will help users to understand and utilize UAM corpus tool critically and provide some inspirations to avoid the influence of its weakness as far as possible, for the sake of reliability and validity of their future study.
GEOCHEMICAL SURVEY AND POTENTIAL MINERALIZATION INVESTIGATION OF ILERO AND ITS ENVIRONS OYO STATE, NIGERIA

Ilero and its environs are part of the Kajola local Government area, Oyo State, and fall within the basement complex of southwestern Nigeria. The research work was focused on the geological mapping of the area and the study of the different rock and minerals units to determine the mineral resources of the area using petrographic, geochemical, and XRD analysis. The geochemical analysis showed the rocks and minerals to be diversely composed of 54-97% SiO2, 0.1-20% Al2O3, 0.8-4% MgO, 0.5-6% Fe2O3, &lt; 1% K2O, TiO2 and minor amounts of trace elements including copper, manganese, and lead. The mineralogy of the rocks and ore mineral comprised of quartz, biotite, hornblende, alkali feldspars, and tourmaline. There are also indications of the presence of chlorite and some ferromagnesian minerals such as pyroxene and olivine. The rocks are predominantly acid rocks along with a few basic rocks.
The Research Data Alliance Interest Group on Agricultural Data: Supporting a Global Community of Practice

Abstract Efforts to address equity and inclusion in agricultural data infrastructures face numerous challenges. People and networks are widely distributed geographically. This means some solutions to data problems may arise regionally and independently, yet many people are not easily able to engage with their distant colleagues to learn about them or collaborate. In general, constraints on funding for such projects are often national rather than international, and travel funding is not equally distributed. Finally, the breadth of activity means interdisciplinary communication is important but difficult and hard to sustain. Addressing these challenges, the Research Data Alliance (RDA) has been a home for the Interest Group on Agricultural Data (IGAD) since 2013. In 2021, IGAD became the first example of a new type of RDA group – a Community of Practice. A future goal is to use this community of practice to put good regional or national work into practice via inclusive collaborations. This chapter reflects on the lessons learnt from the IGAD community of practice in its attempts to include new voices around the world.
Sedimentologika: a community-driven diamond open access journal in sedimentology

Sedimentologika is a community-driven Diamond Open Access (DOA) scientific journal for the publication of work in the broad area of sedimentology and stratigraphy. The journal aims to provide the academic community and society a platform guaranteeing permanent free publication and free access to peer-reviewed scientific studies focusing on all types of sedimentary processes, deposits, and environments across all spatial and temporal scales, on Earth or any other planetary body. Sedimentologika is part of an ongoing broader DOA movement in geosciences aspiring freedom from the financial barriers and pressures of private publishing houses, to provide direct and equal access to science for all citizens, scientists, and institutions worldwide. The published material will include research, review, methods and opinion articles, which will be free to share, as the authors will naturally retain the copyright. The manuscripts will be written in English and authors can attach a second abstract to each submission in the language of their choice, further allowing local communities, students, or decisional bodies to access, at least, a summary of the latest research in a language they understand. This journal is defined by Open Science principles to promote ethical dissemination and accessibility of science and knowledge, following high equity, diversity and inclusion standards. Sedimentologika emerged as a solution for the scientific community to sidestep structural inequality of the currently financially unsustainable academic publishing system and to commit to bibliodiversity. Our objective is to ensure that scientific findings remain accessible to all in order to keep advancing research and informing society on how we understand sedimentology and stratigraphy in the world around us. Sedimentologika is driven by the academic and scientific community for the community and society, promoting self-governance and adapting to the needs expressed by the community.