Reviewerly/exHarmony huggingface dataset:
Forecasting the cryptocurrency exchange rate based on the ranking of expert opinions

To date, most existing cryptocurrency exchanges do not have in their arsenal tools that would allow them to verify and investigate the information disseminated on social networks regarding a particular cryptocurrency. This makes it possible to conduct a relevant research with the subsequent development of a tool that, if used correctly, will provide users with advisory advice on further actions in relation to the cryptocurrency under study in the system. Based on this advice, interested parties will be able to adjust their decisions regarding further financial steps. The basis of most recommender systems is always the need to identify some influencing factors, which are later given certain weights to facilitate and simplify the formulation of further advice for users. In this paper, we study the influence of celebrity publications on the formation of prices for a particular cryptocurrency at a certain point in time. The importance and existence of this influence was previously proven by statistical methods. The purpose of the study is to develop an algorithm for studying the level of influence of posts of each of the selected group of experts in social networks on the cryptocurrency rate. The object of the study is the forecast of cryptocurrency rates. The input data used were the list of experts whose level of influence will be studied, the time interval of the study, the number of posts made by each of the experts in question over the specified period of time, and the actual cryptocurrency rates for the relevant period. The experts were well-known personalities who are either knowledgeable in the field of finance in general and cryptocurrencies in particular, or whose activities are somehow related to a particular cryptocurrency. Research methods. Experts are ranked based on the full probability and Bayesian formulas. Forecasting of cryptocurrency rates in a selected period of time is carried out using the algorithm for forecasting cryptocurrency rates based on expert posts on social networks (AUDSM). To control the accuracy of forecasts, the relative average error is calculated. Recommendations for financial transactions with cryptocurrencies are formed by entering the critical value of the exchange rate and calculating the arithmetic mean of cryptocurrency exchange rates for a specified period of time. Results. As a result of the research, an algorithm has been developed that allows taking into account the impact of the posts of each of the selected ranked group of experts on changes in the rates of a particular cryptocurrency. On the basis of the obtained forecasts, the paper presents a methodology for forming recommendations for financial transactions with them.
Counting Jetons from Old Buryat Burials of the Olkhon Region

The history of the accumulation of materials on counting jetons of the 17th–18th centuries obtained from the burials in the Olkhon region (western coast of Lake Baikal from Cape Elokhin to the Buguldeika village, including Olkhon Island) is considered. Based on the study of literary sources, available archival and collection materials stored in the funds of the Irkutsk State University (excavations of V. V. Pavlutskaya in the 1980s), 8 burials from the Old Buryat cemeteries were identified, in which counting jetons were recorded (more than 244). For the first time, counting jetons from the accompanying inventory of the burial ground Todakta IV are introduced into scientific circulation in full. A generalization and analysis of all currently found counting jetons of the Olkhon region are carried out and their general classification is proposed. To determine the images on some counting jetons and establish the names of the masters who made them, A. A. Pushkarev’s research was used. It was possible to identify 129 jetons with varying degrees of completeness. Among them, according to the plots on the front side, the portrait theme (chest profiles of monarchs) occupies a leading place. There is a variety of plots on the reverse side of the jetons: heraldic signs, an ancient warrior, a park with a fountain, a three-masted ship, a tree under the sun. Most of the counting jetons are marked with the seal of the master Johann Christian Reich (109). There are also works of Johann Friedrich Weidinger (7), Albrecht Hoger (4), Johann Jakob Ditzel (4), Johann Adam Vogel (3) and Cornelius Lauffer (1). Taking into account the periods of activity of these masters, it is possible to outline the chronology of the use of certain plots for decorating jetons. In the first half of the 18th century (along with heraldic signs marked in the 17th century) images are often found: a sailing ship and a tree under the sun; in one case, an ancient warrior was recorded (in combination with the image of Louis XV). The themes of coats of arms and ships were encountered in the second half of the 18th century. In the Old Buryat burials of the Olkhon region, counting jetons originating from different workshops are found together. The latest of them were made in the workshop of Johann Christian Reich, which is probably associated with the intensification of the export of jetons to Russia and Siberia in the second half of the 18th century.
Gender Role and Hate Speech Representation in Web Series

Abstract: In India, media has been an essential component of life. The effect of the media can be seen with this that majority of people across the globe rely on various media platforms to increase consciousness and get information for enjoyment and to gain knowledge about a variety of other global events. Denis McQuail (2000) believes that “the media is accountable for illuminating and fostering systematic exposure, as well as influencing ideas and ideals.” Furthermore, according to the BARC (Broadcast Audience Research Council) Report, 2019, “web series are defined as popular shows with high viewing that cover a wide range of socio-cultural elements of people's life.” There are several types of streaming platforms for entertainment that broadcast 24*7. India much like other jurisdictions has been struggling with the issue of how to control hate speech on the internet. Regulating internet hate speech is a complex issue. The aim of this study is to examine web series in the perspective of Indian society. The stereotypical images of women and hate speech, including abusive language and rude behavior, and discrimination on the basis of religion and caste, have been portrayed in Indian web series. The current study intends to investigate how the Indian web series content structure continues to impact gender role and hate speech representation on streaming platforms.
Fairness-Aware Structured Pruning in Transformers

The increasing size of large language models (LLMs) has introduced challenges in their training and inference. Removing model components is perceived as a solution to tackle the large model sizes, however, existing pruning methods solely focus on performance, without considering an essential aspect for the responsible use of LLMs: model fairness. It is crucial to address the fairness of LLMs towards diverse groups, such as women, Black people, LGBTQ+, Jewish communities, among others, as they are being deployed and available to a wide audience. In this work, first, we investigate how attention heads impact fairness and performance in pre-trained transformer-based language models. We then propose a novel method to prune the attention heads that negatively impact fairness while retaining the heads critical for performance, i.e. language modeling capabilities. Our approach is practical in terms of time and resources, as it does not require fine-tuning the final pruned, and fairer, model. Our findings demonstrate a reduction in gender bias by 19%, 19.5%, 39.5%, 34.7%, 23%, and 8% for DistilGPT-2, GPT-2, GPT-Neo of two different sizes, GPT-J, and Llama 2 models, respectively, in comparison to the biased model, with only a slight decrease in performance.
Guess What Quantum Computing Can Do for Test Case Optimization

In the near term, quantum approximate optimization algorithms (QAOAs) hold great potential to solve combinatorial optimization problems. These are hybrid algorithms, i.e., a combination of quantum and classical algorithms. Several proof-of-concept applications of QAOAs for solving combinatorial problems, such as portfolio optimization, energy optimization in power systems, and job scheduling, have been demonstrated. However, whether QAOAs can efficiently solve optimization problems from classical software engineering, such as test optimization, remains unstudied. To this end, we present the first effort to formulate a software test case optimization problem as a QAOA problem and solve it on quantum computer simulators. To solve bigger test optimization problems that require many qubits, which are unavailable these days, we integrate a problem decomposition strategy with the QAOA. We performed an empirical evaluation with five test case optimization problems and four industrial datasets from ABB, Google, and Orona to compare various configurations of our approach, assess its decomposition strategy of handling large datasets, and compare its performance with classical algorithms (i.e., Genetic Algorithm (GA) and Random Search). Based on the evaluation results, we recommend the best configuration of our approach for test case optimization problems. Also, we demonstrate that our strategy can reach the same effectiveness as GA and outperform GA in two out of five test case optimization problems we conducted.
A Computational Note on the Graphical Ridge in High-dimension

This article explores the estimation of precision matrices in high-dimensional Gaussian graphical models. We address the challenge of improving the accuracy of maximum likelihood-based precision estimation through penalization. Specifically, we consider an elastic net penalty, which incorporates both L1 and Frobenius norm penalties while accounting for the target matrix during estimation. To enhance precision matrix estimation, we propose a novel two-step estimator that combines the strengths of ridge and graphical lasso estimators. Through this approach, we aim to improve overall estimation performance. Our empirical analysis demonstrates the superior efficiency of our proposed method compared to alternative approaches. We validate the effectiveness of our proposal through numerical experiments and application on three real datasets. These examples illustrate the practical applicability and usefulness of our proposed estimator.
Social-Transmotion: Promptable Human Trajectory Prediction

Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating the space. To address this, we introduce Social-Transmotion, a generic model that exploits the power of transformers to handle diverse and numerous visual cues, capturing the multi-modal nature of human behavior. We translate the idea of a prompt from Natural Language Processing (NLP) to the task of human trajectory prediction, where a prompt can be a sequence of x-y coordinates on the ground, bounding boxes or body poses. This, in turn, augments trajectory data, leading to enhanced human trajectory prediction. Our model exhibits flexibility and adaptability by capturing spatiotemporal interactions between pedestrians based on the available visual cues, whether they are poses, bounding boxes, or a combination thereof. By the masking technique, we ensure our model's effectiveness even when certain visual cues are unavailable, although performance is further boosted with the presence of comprehensive visual data. We delve into the merits of using 2d versus 3d poses, and a limited set of poses. Additionally, we investigate the spatial and temporal attention map to identify which keypoints and frames of poses are vital for optimizing human trajectory prediction. Our approach is validated on multiple datasets, including JTA, JRDB, Pedestrians and Cyclists in Road Traffic, and ETH-UCY. The code is publicly available: https://github.com/vita-epfl/social-transmotion
Automatic LPI Radar Waveform Recognition Using Vision Transformer

This paper investigates the classification of low probability of intercept (LPI) radar signals by exploiting the intrinsic advantages of the Vision Transformer (ViT). Due to the characteristics of LPI radar signals, such as intrapulse modulation, wide frequency bands, and low transmission power, these signals are challenging to be detected and classified using traditional analytic methods. This has led to the adoption of various deep learning techniques to overcome these limitations. On the one hand, the ViT, originally developed for natural language processing, has demonstrated outstanding performance in computer vision by replacing the structure of the convolutional neural network (CNN) with the transformer, specifically leveraging self-attention. Therefore, this paper explores a method based on the ViT technique for classifying LPI signal images. The simulation results show that the proposed ViT method outperforms the traditional CNN method by 12.8% at −10dB SNR.
APPLICATION OF THE SCRUM METHODOLOGY TO IMPLEMENT STANDARDIZED PROJECT DOCUMENTATION: CASE STUDY IN A SUPPLY CHAIN MANAGEMENT CONSULTING COMPANY

This article presents a case study carried out in the Supply Chain and Purchasing Management department at the French consulting firm Altran Technologies. Due to the incessant search to better satisfy the expectations of its customers, the object company decided to implement a standard of services aimed at serving its customers. Therefore, this article aims to apply the scrum methodology to implement standardized project documentation in a supply chain and purchasing management-consulting company. In this way, this project was carried out according to the scrum methodology and used the Trello tool as a support tool. Thus, the documentation was created dynamically, which made the project enjoyable for the collaborators, who at times even finished their deliverables even before the deadline. Finally, it was considered that this form of standardization of service offers satisfaction in meeting demands both for the external public and for the company's internal public.
Evaluation of the Local Content Learning Program for Local Language in Jayapura District Using the CIPP Evaluation Model

Local governments in Indonesia through schools are starting to be moved to teach local languages as local content lessons to protect local local languages. Jayapura district also implements local content of the local language. This study aims to evaluate the Local Language Learning Program in Jayapura District. This research was evaluative research with CIPP model and using a qualitative approach. The data analysis technique used was Miles and Huberman. The formulation of the problem in this study was that the Regional Language Local Content Learning program in Jayapura Regency has been running since 2022 and, in fact, faces various obstacles; for this reason, it is necessary to conduct a thorough evaluation research on this program. Data collection techniques in this study were carried out by means of interviews, documentation studies, and observations. The results obtained in this study include in the context dimension, it is found that the local language local content program in Jayapura Regency was implemented quite well. In the input dimension, this program is also in the sufficient category. The process dimension in this study is also in the sufficient category. Then the product evaluation, has less results.
YOLOv5 and U-Net-based Character Detection for Nusantara Script

Indonesia boasts a diverse range of indigenous scripts, called Nusantara scripts, which encompass Bali, Batak, Bugis, Javanese, Kawi, Kerinci, Lampung, Pallava, Rejang, and Sundanese scripts. However, prevailing character detection techniques predominantly cater to Latin or Chinese scripts. In an extension of our prior work, which concentrated on the classification of script types and character recognition within Nusantara script systems, this study advances our research by integrating object detection techniques, employing the YOLOv5 model, and enhancing performance through the incorporation of the U-Net model to facilitate the pinpointing of fundamental Nusantara script's character locations within input document images. Subsequently, our investigation delves into rearranging these character positions in alignment with the distinctive styles of Nusantara scripts. Experimental results reveal YOLOv5's performance, yielding a loss rate of approximately 0.05 in character location detection. Concurrently, the U-Net model exhibits an accuracy ranging from 75% to 90% for predicting character regions. While YOLOv5 may not achieve flawless detection of all Nusantara scripts, integrating the U-Net model significantly enhances the detection rate by 1.2%.
Shift Registers and More

In this chapter we will look at some useful sequential logic circuits. We will also look at circuits that make use of the D-type latch.
Agile software development approach for 'ad-hoc' IT projects

Restrictive Scrum assumptions make the effectiveness of this approach debatable in projects deviating from typical execution conditions. This article delivers a comprehensive software development approach for both academic and commercial Information Technology (IT) projects effectuated by teams that are hampered by significantly unsystematic participation of project members and mercurial internal communication. The nature of ‘ad-hoc’ projects imposes another level of difficulty in terms of both managing the conduct of such a project and ensuring the quality of the end product. Multicyclic action research enabled a gradual adaptation of the Scrum approach to support such project conditions. This study introduces major alterations to Sprint implementation and minor enhancements within the documentation process to streamline knowledge sharing among Development Team members. Proposed key alterations include the evolution of Daily Scrum towards Weekly Scrum, the possibility of extending Sprints length, the eventuality to switch team members during Sprint due to substantial failure to meet deadlines, having at least two team members responsible for a single Product Backlog Item (PBI) at all times, as well as exclusion of Burndown Chart in favor for Development Team members updating their working time. Positive validation of enhancements in mixed settings confirms that the generic Scrum framework can be adapted to support highly volatile projects. The proposed approach is suitable not only for carrying out software development initiatives that rely heavily on the skills of external experts and/or volunteers. It also supports traditional Scrum teams that seek to reduce their exposure to risk arising from organizational changes.
Requirements for a teacher-mentor in the works of K. D. Ushinsky and modern authors: comparative analysis

This article describes a study devoted to the comparative analysis of modern requirements for a teacher-mentor and requirements for him in the works of an outstanding Russian teacher K.D. Ushinsky. The purpose of the study is to analyze the modern requirements for a teacher-mentor in comparison with the requirements of K.D. Ushinsky. The article reveals the stages of research: analysis of the works of K.D. Ushinsky «A guide to teaching on the «Native word», «The project of the teachers' seminary», «Preface to the first volume of «Pedagogical Anthropology», «Native word. A book for teachers», a comparative analysis of modern requirements for a teacher-mentor and the requirements for him by K.D. Ushinsky, generalization of research results and formulation of conclusions. The article reveals the stages of research: analysis of the works of K.D. Ushinsky «A guide to teaching on the «Native word», «The project of the teachers' seminary», «Preface to the first volume of "Pedagogical Anthropology», «Native word. A book for teachers», a comparative analysis of modern requirements for a teacher-mentor and the requirements for him by K.D. Ushinsky, generalization of research results and formulation of conclusions. The article analyzes the pedagogical works of K.D. Ushinsky and describes his requirements for a mentor as a teacher and educator, reveals the modern understanding of mentoring by the authors as professional support of a young (novice) teacher by a more experienced mentor colleague. K.D. Ushinsky in the «Guide to teaching on the «Native Word» imposes special requirements on the mentor – primary school teacher – awareness of mastering the native language, correct, literate speech, learning to understand oral and written speech, teaching students to express their thoughts in writing. In the «Teacher's Seminary Project», K.D. Ushinsky points out that a mentor should have not only professional knowledge, but also skills, as well as readiness to carry out his duties. According to K.D. Ushinsky, a teacher-mentor should have patience and special knowledge, as well as pedagogical tact and experience. K.D. Ushinsky places high demands on a teacher-mentor. His pedagogical ideas can be applied in the modern professional education of future teachers and in the mentoring activities of novice teachers.
Representative Virtual Material Collections about University Scientists: The Experience of the Uzhhorod National University Library

Objective. The research is aimed at studying practical experience of creation and application of the representations of virtual material collections about the scientists of the Uzhhorod National University, as one of the important popularization mechanisms of the university science. Methods. Using our own developments, we attempted to familiarize the library community with the specialized methodology of representation work of the scientific library of the Uzhhorod National University during quarantine restrictions and martial law in Ukraine. Using the comparative analysis, the efficiency of the representations of virtual material collections, created by the library as publicizing the development of university science and culture of the region and the interest of remote users in them has been proven. Results. The substantiation of the obtained results is based on the characteristics of the Uzhhorod National University library during remote work of the institution, aimed at increasing the interest of virtual users in the content of the library. The efficiency of using the method of representations of information products of libraries during the period of difficult physical access to the library funds of Ukraine has been confirmed. Analysis of the expansion of the library’s information services and the practical recommendations regarding the active popularization of scientists and prominent figures of the Zakarpattia region are considered as one of the methods of reorienting the work of the library and its services in accordance with today’s challenges. Conclusions. The important role of library support in the popularization of science and culture of the region, as an important factor of practical library assistance to society during the times of trials for Ukraine, has been confirmed.